diff --git a/README.md b/README.md
index ddd2ce0c65c93df7f2f50872da40c76f49f1e00e..ec997b9a6a30fdb73455b5ad3d92176b02534228 100644
--- a/README.md
+++ b/README.md
@@ -3,24 +3,19 @@ annotations_creators:
 - expert-generated
 - crowdsourced
 - found
-language:
-- en
 language_creators:
 - crowdsourced
 - expert-generated
+language:
+- en
 license:
 - cc-by-4.0
 multilinguality:
 - monolingual
-pretty_name: newyorker_caption_contest
 size_categories:
 - 1K<n<10K
 source_datasets:
 - original
-tags:
-- humor
-- caption contest
-- new yorker
 task_categories:
 - image-to-text
 - multiple-choice
@@ -34,6 +29,1233 @@ task_ids:
 - language-modeling
 - visual-question-answering
 - explanation-generation
+pretty_name: newyorker_caption_contest
+tags:
+- humor
+- caption contest
+- new yorker
+dataset_info:
+- config_name: explanation
+  features:
+  - name: image
+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: image_location
+    dtype: string
+  - name: image_description
+    dtype: string
+  - name: image_uncanny_description
+    dtype: string
+  - name: entities
+    sequence: string
+  - name: questions
+    sequence: string
+  - name: caption_choices
+    dtype: string
+  - name: from_description
+    dtype: string
+  - name: label
+    dtype: string
+  - name: n_tokens_label
+    dtype: int32
+  - name: instance_id
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 133827514.64
+    num_examples: 2340
+  - name: validation
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+    num_examples: 130
+  - name: test
+    num_bytes: 6863533.0
+    num_examples: 131
+  download_size: 139737042
+  dataset_size: 148730932.64
+- config_name: explanation_1
+  features:
+  - name: image
+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: image_location
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+  - name: image_description
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+  - name: image_uncanny_description
+    dtype: string
+  - name: entities
+    sequence: string
+  - name: questions
+    sequence: string
+  - name: caption_choices
+    dtype: string
+  - name: from_description
+    dtype: string
+  - name: label
+    dtype: string
+  - name: n_tokens_label
+    dtype: int32
+  - name: instance_id
+    dtype: string
+  splits:
+  - name: train
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+  - name: validation
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+    num_examples: 128
+  - name: test
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+    num_examples: 130
+  download_size: 134637839
+  dataset_size: 152566212.45999998
+- config_name: explanation_2
+  features:
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+    dtype: image
+  - name: contest_number
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+  - name: image_location
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+  - name: image_description
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+    dtype: string
+  - name: entities
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+  - name: questions
+    sequence: string
+  - name: caption_choices
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+  - name: from_description
+    dtype: string
+  - name: label
+    dtype: string
+  - name: n_tokens_label
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+  - name: instance_id
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+    num_examples: 132
+  - name: test
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+    num_examples: 128
+  download_size: 138271185
+  dataset_size: 153709976.342
+- config_name: explanation_3
+  features:
+  - name: image
+    dtype: image
+  - name: contest_number
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+  - name: questions
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+  - name: test
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+    num_examples: 132
+  download_size: 136862726
+  dataset_size: 153619845.342
+- config_name: explanation_4
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+  - name: test
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+- config_name: explanation_from_pixels
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+  - name: image
+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: caption_choices
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+- config_name: explanation_from_pixels_1
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+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: caption_choices
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+- config_name: explanation_from_pixels_2
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+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: caption_choices
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+- config_name: explanation_from_pixels_3
+  features:
+  - name: image
+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: caption_choices
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+- config_name: explanation_from_pixels_4
+  features:
+  - name: image
+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: caption_choices
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+- config_name: matching
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+- config_name: matching_1
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+- config_name: matching_2
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+- config_name: matching_3
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+    num_bytes: 593388719.232
+    num_examples: 9432
+  - name: validation
+    num_bytes: 28907567.0
+    num_examples: 513
+  - name: test
+    num_bytes: 34072817.0
+    num_examples: 531
+  download_size: 562902941
+  dataset_size: 656369103.232
+- config_name: ranking_from_pixels
+  features:
+  - name: image
+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: caption_choices
+    sequence: string
+  - name: winner_source
+    dtype: string
+  - name: label
+    dtype: string
+  - name: n_tokens_label
+    dtype: int32
+  - name: instance_id
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 101282973.752
+    num_examples: 1596
+  - name: validation
+    num_bytes: 32072331.0
+    num_examples: 506
+  - name: test
+    num_bytes: 28550057.0
+    num_examples: 513
+  download_size: 134283256
+  dataset_size: 161905361.752
+- config_name: ranking_from_pixels_1
+  features:
+  - name: image
+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: caption_choices
+    sequence: string
+  - name: winner_source
+    dtype: string
+  - name: label
+    dtype: string
+  - name: n_tokens_label
+    dtype: int32
+  - name: instance_id
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 93123370.15
+    num_examples: 1575
+  - name: validation
+    num_bytes: 34965110.0
+    num_examples: 534
+  - name: test
+    num_bytes: 32072331.0
+    num_examples: 506
+  download_size: 130879365
+  dataset_size: 160160811.15
+- config_name: ranking_from_pixels_2
+  features:
+  - name: image
+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: caption_choices
+    sequence: string
+  - name: winner_source
+    dtype: string
+  - name: label
+    dtype: string
+  - name: n_tokens_label
+    dtype: int32
+  - name: instance_id
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 93496576.85
+    num_examples: 1550
+  - name: validation
+    num_bytes: 32145436.0
+    num_examples: 531
+  - name: test
+    num_bytes: 34965110.0
+    num_examples: 534
+  download_size: 131637359
+  dataset_size: 160607122.85
+- config_name: ranking_from_pixels_3
+  features:
+  - name: image
+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: caption_choices
+    sequence: string
+  - name: winner_source
+    dtype: string
+  - name: label
+    dtype: string
+  - name: n_tokens_label
+    dtype: int32
+  - name: instance_id
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 93840620.26
+    num_examples: 1553
+  - name: validation
+    num_bytes: 33718821.0
+    num_examples: 531
+  - name: test
+    num_bytes: 32145436.0
+    num_examples: 531
+  download_size: 133214495
+  dataset_size: 159704877.26
+- config_name: ranking_from_pixels_4
+  features:
+  - name: image
+    dtype: image
+  - name: contest_number
+    dtype: int32
+  - name: caption_choices
+    sequence: string
+  - name: winner_source
+    dtype: string
+  - name: label
+    dtype: string
+  - name: n_tokens_label
+    dtype: int32
+  - name: instance_id
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 99008131.43
+    num_examples: 1571
+  - name: validation
+    num_bytes: 28550057.0
+    num_examples: 513
+  - name: test
+    num_bytes: 33718821.0
+    num_examples: 531
+  download_size: 136230399
+  dataset_size: 161277009.43
+configs:
+- config_name: explanation
+  data_files:
+  - split: train
+    path: explanation/train-*
+  - split: validation
+    path: explanation/validation-*
+  - split: test
+    path: explanation/test-*
+- config_name: explanation_1
+  data_files:
+  - split: train
+    path: explanation_1/train-*
+  - split: validation
+    path: explanation_1/validation-*
+  - split: test
+    path: explanation_1/test-*
+- config_name: explanation_2
+  data_files:
+  - split: train
+    path: explanation_2/train-*
+  - split: validation
+    path: explanation_2/validation-*
+  - split: test
+    path: explanation_2/test-*
+- config_name: explanation_3
+  data_files:
+  - split: train
+    path: explanation_3/train-*
+  - split: validation
+    path: explanation_3/validation-*
+  - split: test
+    path: explanation_3/test-*
+- config_name: explanation_4
+  data_files:
+  - split: train
+    path: explanation_4/train-*
+  - split: validation
+    path: explanation_4/validation-*
+  - split: test
+    path: explanation_4/test-*
+- config_name: explanation_from_pixels
+  data_files:
+  - split: train
+    path: explanation_from_pixels/train-*
+  - split: validation
+    path: explanation_from_pixels/validation-*
+  - split: test
+    path: explanation_from_pixels/test-*
+- config_name: explanation_from_pixels_1
+  data_files:
+  - split: train
+    path: explanation_from_pixels_1/train-*
+  - split: validation
+    path: explanation_from_pixels_1/validation-*
+  - split: test
+    path: explanation_from_pixels_1/test-*
+- config_name: explanation_from_pixels_2
+  data_files:
+  - split: train
+    path: explanation_from_pixels_2/train-*
+  - split: validation
+    path: explanation_from_pixels_2/validation-*
+  - split: test
+    path: explanation_from_pixels_2/test-*
+- config_name: explanation_from_pixels_3
+  data_files:
+  - split: train
+    path: explanation_from_pixels_3/train-*
+  - split: validation
+    path: explanation_from_pixels_3/validation-*
+  - split: test
+    path: explanation_from_pixels_3/test-*
+- config_name: explanation_from_pixels_4
+  data_files:
+  - split: train
+    path: explanation_from_pixels_4/train-*
+  - split: validation
+    path: explanation_from_pixels_4/validation-*
+  - split: test
+    path: explanation_from_pixels_4/test-*
+- config_name: matching
+  data_files:
+  - split: train
+    path: matching/train-*
+  - split: validation
+    path: matching/validation-*
+  - split: test
+    path: matching/test-*
+- config_name: matching_1
+  data_files:
+  - split: train
+    path: matching_1/train-*
+  - split: validation
+    path: matching_1/validation-*
+  - split: test
+    path: matching_1/test-*
+- config_name: matching_2
+  data_files:
+  - split: train
+    path: matching_2/train-*
+  - split: validation
+    path: matching_2/validation-*
+  - split: test
+    path: matching_2/test-*
+- config_name: matching_3
+  data_files:
+  - split: train
+    path: matching_3/train-*
+  - split: validation
+    path: matching_3/validation-*
+  - split: test
+    path: matching_3/test-*
+- config_name: matching_4
+  data_files:
+  - split: train
+    path: matching_4/train-*
+  - split: validation
+    path: matching_4/validation-*
+  - split: test
+    path: matching_4/test-*
+- config_name: matching_from_pixels
+  data_files:
+  - split: train
+    path: matching_from_pixels/train-*
+  - split: validation
+    path: matching_from_pixels/validation-*
+  - split: test
+    path: matching_from_pixels/test-*
+- config_name: matching_from_pixels_1
+  data_files:
+  - split: train
+    path: matching_from_pixels_1/train-*
+  - split: validation
+    path: matching_from_pixels_1/validation-*
+  - split: test
+    path: matching_from_pixels_1/test-*
+- config_name: matching_from_pixels_2
+  data_files:
+  - split: train
+    path: matching_from_pixels_2/train-*
+  - split: validation
+    path: matching_from_pixels_2/validation-*
+  - split: test
+    path: matching_from_pixels_2/test-*
+- config_name: matching_from_pixels_3
+  data_files:
+  - split: train
+    path: matching_from_pixels_3/train-*
+  - split: validation
+    path: matching_from_pixels_3/validation-*
+  - split: test
+    path: matching_from_pixels_3/test-*
+- config_name: matching_from_pixels_4
+  data_files:
+  - split: train
+    path: matching_from_pixels_4/train-*
+  - split: validation
+    path: matching_from_pixels_4/validation-*
+  - split: test
+    path: matching_from_pixels_4/test-*
+- config_name: ranking
+  data_files:
+  - split: train
+    path: ranking/train-*
+  - split: validation
+    path: ranking/validation-*
+  - split: test
+    path: ranking/test-*
+- config_name: ranking_1
+  data_files:
+  - split: train
+    path: ranking_1/train-*
+  - split: validation
+    path: ranking_1/validation-*
+  - split: test
+    path: ranking_1/test-*
+- config_name: ranking_2
+  data_files:
+  - split: train
+    path: ranking_2/train-*
+  - split: validation
+    path: ranking_2/validation-*
+  - split: test
+    path: ranking_2/test-*
+- config_name: ranking_3
+  data_files:
+  - split: train
+    path: ranking_3/train-*
+  - split: validation
+    path: ranking_3/validation-*
+  - split: test
+    path: ranking_3/test-*
+- config_name: ranking_4
+  data_files:
+  - split: train
+    path: ranking_4/train-*
+  - split: validation
+    path: ranking_4/validation-*
+  - split: test
+    path: ranking_4/test-*
+- config_name: ranking_from_pixels
+  data_files:
+  - split: train
+    path: ranking_from_pixels/train-*
+  - split: validation
+    path: ranking_from_pixels/validation-*
+  - split: test
+    path: ranking_from_pixels/test-*
+- config_name: ranking_from_pixels_1
+  data_files:
+  - split: train
+    path: ranking_from_pixels_1/train-*
+  - split: validation
+    path: ranking_from_pixels_1/validation-*
+  - split: test
+    path: ranking_from_pixels_1/test-*
+- config_name: ranking_from_pixels_2
+  data_files:
+  - split: train
+    path: ranking_from_pixels_2/train-*
+  - split: validation
+    path: ranking_from_pixels_2/validation-*
+  - split: test
+    path: ranking_from_pixels_2/test-*
+- config_name: ranking_from_pixels_3
+  data_files:
+  - split: train
+    path: ranking_from_pixels_3/train-*
+  - split: validation
+    path: ranking_from_pixels_3/validation-*
+  - split: test
+    path: ranking_from_pixels_3/test-*
+- config_name: ranking_from_pixels_4
+  data_files:
+  - split: train
+    path: ranking_from_pixels_4/train-*
+  - split: validation
+    path: ranking_from_pixels_4/validation-*
+  - split: test
+    path: ranking_from_pixels_4/test-*
 ---
 
 # Dataset Card for New Yorker Caption Contest Benchmarks
diff --git a/dataset_infos.json b/dataset_infos.json
deleted file mode 100644
index 2204edba00e250cb5ee5ab37de8b321be2d24bad..0000000000000000000000000000000000000000
--- a/dataset_infos.json
+++ /dev/null
@@ -1 +0,0 @@
-{"matching": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "matching", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 13544991, "num_examples": 9792, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 687342, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 687942, "num_examples": 528, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching.zip": {"num_bytes": 3374031, "checksum": "e854c62b8802802fecacc437c3cae2f62b1bbc55683898090720ba88c1d93233"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 42897240, "post_processing_size": null, "dataset_size": 14920275, "size_in_bytes": 57817515}, "matching_from_pixels": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "matching_from_pixels", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 762740, "num_examples": 1632, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 244136, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 243528, "num_examples": 528, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels.zip": {"num_bytes": 307725, "checksum": "0ae2d1c3a2ddfc0873ef993247b1c184ade37ef2f72fb59984116d1696577bb1"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39830934, "post_processing_size": null, "dataset_size": 1250404, "size_in_bytes": 41081338}, "ranking": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "winner_source": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "ranking", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10503648, "num_examples": 9576, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 516533, "num_examples": 507, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 527159, "num_examples": 513, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking.zip": {"num_bytes": 2440380, "checksum": "d100c437d7f77c5582b1cf3b73a2c9111e3870e323a6ac40ce6be434c1091829"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 41963589, "post_processing_size": null, "dataset_size": 11547340, "size_in_bytes": 53510929}, "ranking_from_pixels": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "winner_source": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "ranking_from_pixels", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 531704, "num_examples": 1596, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 167378, "num_examples": 506, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 169649, "num_examples": 513, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels.zip": {"num_bytes": 203854, "checksum": "6afb6dd49b9558091ce09e4dea0d09a101049bd59ed6d26567cfa3401e60682c"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39727063, "post_processing_size": null, "dataset_size": 868731, "size_in_bytes": 40595794}, "explanation": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"dtype": "string", "id": null, "_type": "Value"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "explanation", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3074876, "num_examples": 2340, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 160986, "num_examples": 130, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 162089, "num_examples": 131, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation.zip": {"num_bytes": 856934, "checksum": "7b4b8428887febaaa320c1e01a5271709c7db7a65aeb3c262d6a68b7d9f5f11f"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 40380143, "post_processing_size": null, "dataset_size": 3397951, "size_in_bytes": 43778094}, "explanation_from_pixels": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "explanation_from_pixels", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 235831, "num_examples": 390, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 77283, "num_examples": 130, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 77448, "num_examples": 131, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels.zip": {"num_bytes": 122918, "checksum": "1c9c3a65bd255c7bccfbf394b266c781bb3762b4a318c5cff8f3da0bfeea75a7"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39646127, "post_processing_size": null, "dataset_size": 390562, "size_in_bytes": 40036689}, "matching_1": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "matching_1", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 13371152, "num_examples": 9684, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 708793, "num_examples": 546, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 687342, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_1.zip": {"num_bytes": 3338401, "checksum": "9c0e4d60efda7aee8d68d3d8e042c473de8ad10f41f0dcfaeda0ba3d408b1a50"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 42861610, "post_processing_size": null, "dataset_size": 14767287, "size_in_bytes": 57628897}, "matching_from_pixels_1": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "matching_from_pixels_1", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 753277, "num_examples": 1614, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 252992, "num_examples": 546, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 244136, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels_1.zip": {"num_bytes": 309284, "checksum": "2f475c11773b733d3c1c21a618a656fd403af0a1bff460db317fd8137ce1676d"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39832493, "post_processing_size": null, "dataset_size": 1250405, "size_in_bytes": 41082898}, "ranking_1": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "winner_source": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "ranking_1", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10360371, "num_examples": 9450, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 544050, "num_examples": 534, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 516533, "num_examples": 507, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_1.zip": {"num_bytes": 2415555, "checksum": "06858a8a18bdc6e5787ab4621f4d7b17939081cfb6240ee4dd896c678cc79ca1"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 41938764, "post_processing_size": null, "dataset_size": 11420954, "size_in_bytes": 53359718}, "ranking_from_pixels_1": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "winner_source": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "ranking_from_pixels_1", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 524392, "num_examples": 1575, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 176960, "num_examples": 534, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 167378, "num_examples": 506, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels_1.zip": {"num_bytes": 203613, "checksum": "8401739c8485d893bb05246424b3c0fc6b539c6e311a92a47a7ec0fb9528a6af"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39726822, "post_processing_size": null, "dataset_size": 868730, "size_in_bytes": 40595552}, "explanation_1": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"dtype": "string", "id": null, "_type": "Value"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "explanation_1", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3086994, "num_examples": 2358, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 158658, "num_examples": 128, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 160986, "num_examples": 130, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_1.zip": {"num_bytes": 861520, "checksum": "4722a0f09564f774a69199c2753d6696189e297bd8c75244e86c15432087e01c"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 40384729, "post_processing_size": null, "dataset_size": 3406638, "size_in_bytes": 43791367}, "explanation_from_pixels_1": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "explanation_from_pixels_1", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 235060, "num_examples": 393, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 78219, "num_examples": 128, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 77283, "num_examples": 130, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels_1.zip": {"num_bytes": 122627, "checksum": "0ef48fc4c94c6bbceecc87cd22848936d49ca7ac6c85ed04d141aeff4c5dd87c"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39645836, "post_processing_size": null, "dataset_size": 390562, "size_in_bytes": 40036398}, "matching_2": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "matching_2", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 13248994, "num_examples": 9630, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 714032, "num_examples": 540, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 708793, "num_examples": 546, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_2.zip": {"num_bytes": 3311397, "checksum": "85d489d20c91e6db9ee2c9f9fa5ae44802d49a740889c49dc61191ceced2635e"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 42834606, "post_processing_size": null, "dataset_size": 14671819, "size_in_bytes": 57506425}, "matching_from_pixels_2": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "matching_from_pixels_2", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 744559, "num_examples": 1605, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 252854, "num_examples": 540, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 252992, "num_examples": 546, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels_2.zip": {"num_bytes": 307348, "checksum": "698de8c979f1b134647ddfac66dfecbc081e4e2f8f27fe5a4e7ec332c67e8614"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39830557, "post_processing_size": null, "dataset_size": 1250405, "size_in_bytes": 41080962}, "ranking_2": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "winner_source": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "ranking_2", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10183446, "num_examples": 9306, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 551023, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 544050, "num_examples": 534, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_2.zip": {"num_bytes": 2380230, "checksum": "e125304613056eeda04690bb68b50921ea9871ca299f37c95f61624fd74fdafb"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 41903439, "post_processing_size": null, "dataset_size": 11278519, "size_in_bytes": 53181958}, "ranking_from_pixels_2": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "winner_source": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "ranking_from_pixels_2", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 514484, "num_examples": 1550, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 177286, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 176960, "num_examples": 534, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels_2.zip": {"num_bytes": 203718, "checksum": "2949692ace6eb2162fffaff17a88898d2d608dcfdc2d04861c23ec05b87ef6c5"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39726927, "post_processing_size": null, "dataset_size": 868730, "size_in_bytes": 40595657}, "explanation_2": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"dtype": "string", "id": null, "_type": "Value"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "explanation_2", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3074106, "num_examples": 2346, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 163651, "num_examples": 132, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 158658, "num_examples": 128, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_2.zip": {"num_bytes": 861915, "checksum": "14ed5f81c51718486b10716cf9f714c756bdf0c89e50bb958c16a58b1ea09320"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 40385124, "post_processing_size": null, "dataset_size": 3396415, "size_in_bytes": 43781539}, "explanation_from_pixels_2": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "explanation_from_pixels_2", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 232956, "num_examples": 391, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 79386, "num_examples": 132, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 78219, "num_examples": 128, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels_2.zip": {"num_bytes": 122669, "checksum": "e51447c1c4a760d47c0c647fc203d96295ae06ad87166c3a6db383eaa3f7e78e"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39645878, "post_processing_size": null, "dataset_size": 390561, "size_in_bytes": 40036439}, "matching_3": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "matching_3", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 13262428, "num_examples": 9630, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 706095, "num_examples": 546, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 714032, "num_examples": 540, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_3.zip": {"num_bytes": 3307856, "checksum": "21f934f5b7db7864856878346c1a30112dbe479a594e42db2867c88e5cfe2a57"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 42831065, "post_processing_size": null, "dataset_size": 14682555, "size_in_bytes": 57513620}, "matching_from_pixels_3": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "matching_from_pixels_3", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 740655, "num_examples": 1605, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 256896, "num_examples": 546, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 252854, "num_examples": 540, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels_3.zip": {"num_bytes": 308596, "checksum": "8e30f3c272550883e989fa36f0957b860b38a689dea3d6ea2fed71403feddeca"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39831805, "post_processing_size": null, "dataset_size": 1250405, "size_in_bytes": 41082210}, "ranking_3": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "winner_source": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "ranking_3", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10257068, "num_examples": 9324, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 531455, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 551023, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_3.zip": {"num_bytes": 2390643, "checksum": "f2f65f144fa70b0717b7c05efc7926e9fdbfb96f946f7ad2eb8ca4ff248826dc"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 41913852, "post_processing_size": null, "dataset_size": 11339546, "size_in_bytes": 53253398}, "ranking_from_pixels_3": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "winner_source": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "ranking_from_pixels_3", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 513986, "num_examples": 1553, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 177459, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 177286, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels_3.zip": {"num_bytes": 203557, "checksum": "80b1f658c19dd021f7f3f357cc39a643ec1683a022e2c81e7db2eef458824468"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39726766, "post_processing_size": null, "dataset_size": 868731, "size_in_bytes": 40595497}, "explanation_3": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"dtype": "string", "id": null, "_type": "Value"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "explanation_3", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3072628, "num_examples": 2334, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 158611, "num_examples": 130, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 163651, "num_examples": 132, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_3.zip": {"num_bytes": 860977, "checksum": "0d09e7c18ac10259f5fc0a7e79bdb2ead04debf8ce65d1da1b90f721cc6daaad"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 40384186, "post_processing_size": null, "dataset_size": 3394890, "size_in_bytes": 43779076}, "explanation_from_pixels_3": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "explanation_from_pixels_3", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 232949, "num_examples": 389, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 78227, "num_examples": 130, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 79386, "num_examples": 132, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels_3.zip": {"num_bytes": 123039, "checksum": "6aee346705346f7ccc46adccfa89882847744b77b882825364dca0b16a0cf94a"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39646248, "post_processing_size": null, "dataset_size": 390562, "size_in_bytes": 40036810}, "matching_4": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "matching_4", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 13402726, "num_examples": 9702, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 687942, "num_examples": 528, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 706095, "num_examples": 546, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_4.zip": {"num_bytes": 3339066, "checksum": "3f8f072087ba28a0a49c4ed068eef17dd41f8737a7f690c850c36efcb3d6441e"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 42862275, "post_processing_size": null, "dataset_size": 14796763, "size_in_bytes": 57659038}, "matching_from_pixels_4": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "matching_from_pixels_4", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 749981, "num_examples": 1617, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 243528, "num_examples": 528, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 256896, "num_examples": 546, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels_4.zip": {"num_bytes": 307932, "checksum": "cecbce805b551669534abb39e49f5fc8cac2d8b3a84d48555db19bc01992b2dd"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39831141, "post_processing_size": null, "dataset_size": 1250405, "size_in_bytes": 41081546}, "ranking_4": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "winner_source": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "ranking_4", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10382406, "num_examples": 9432, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 527159, "num_examples": 513, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 531455, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_4.zip": {"num_bytes": 2413757, "checksum": "b3cf071c6046ece7c7a4dd1fb430a7cad8debdebfdcc7c7b2b6efb40fd0d4cfa"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 41936966, "post_processing_size": null, "dataset_size": 11441020, "size_in_bytes": 53377986}, "ranking_from_pixels_4": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "caption_choices": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "winner_source": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "ranking_from_pixels_4", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 521623, "num_examples": 1571, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 169649, "num_examples": 513, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 177459, "num_examples": 531, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels_4.zip": {"num_bytes": 203752, "checksum": "79e83d153f410977e4cac58fc870ca0d9f8ae6e4748bfa21426dc57d66efd437"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 39726961, "post_processing_size": null, "dataset_size": 868731, "size_in_bytes": 40595692}, "explanation_4": {"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n", "citation": "@article{hessel2022androids,\n  title={Do Androids Laugh at Electric Sheep? Humor\" Understanding\" Benchmarks from The New Yorker Caption Contest},\n  author={Hessel, Jack and Marasovi{'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},\n  journal={arXiv preprint arXiv:2209.06293},\n  year={2022}\n}\n\nwww.capcon.dev\n\nOur data contributions are:\n\n- The cartoon-level annotations;\n- The joke explanations;\n- and the framing of the tasks\nWe release these data we contribute under CC-BY (see DATASET_LICENSE).\n\nIf you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:\n\n@misc{newyorkernextmldataset,\n  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},\n  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},\n  year={2020},\n  url={https://nextml.github.io/caption-contest-data/}\n}\n\n@inproceedings{radev-etal-2016-humor,\n  title = \"Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest\",\n  author = \"Radev, Dragomir  and\n      Stent, Amanda  and\n      Tetreault, Joel  and\n      Pappu, Aasish  and\n      Iliakopoulou, Aikaterini  and\n      Chanfreau, Agustin  and\n      de Juan, Paloma  and\n      Vallmitjana, Jordi  and\n      Jaimes, Alejandro  and\n      Jha, Rahul  and\n      Mankoff, Robert\",\n  booktitle = \"LREC\",\n  year = \"2016\",\n}\n\n@inproceedings{shahaf2015inside,\n  title={Inside jokes: Identifying humorous cartoon captions},\n  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},\n  booktitle={KDD},\n  year={2015},\n}\n", "homepage": "www.capcon.dev", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "contest_number": {"dtype": "int32", "id": null, "_type": "Value"}, "image_location": {"dtype": "string", "id": null, "_type": "Value"}, "image_description": {"dtype": "string", "id": null, "_type": "Value"}, "image_uncanny_description": {"dtype": "string", "id": null, "_type": "Value"}, "entities": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "caption_choices": {"dtype": "string", "id": null, "_type": "Value"}, "from_description": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "n_tokens_label": {"dtype": "int32", "id": null, "_type": "Value"}, "instance_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "newyorker_caption_contest", "config_name": "explanation_4", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3084810, "num_examples": 2340, "dataset_name": "newyorker_caption_contest"}, "validation": {"name": "validation", "num_bytes": 162089, "num_examples": 131, "dataset_name": "newyorker_caption_contest"}, "test": {"name": "test", "num_bytes": 158611, "num_examples": 130, "dataset_name": "newyorker_caption_contest"}}, "download_checksums": {"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_4.zip": {"num_bytes": 861773, "checksum": "f5fcf62641a6c844a56ec0a79ec981977442535f197f9c407c3eb7c1a320252d"}, "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {"num_bytes": 39523209, "checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"}}, "download_size": 40384982, "post_processing_size": null, "dataset_size": 3405510, "size_in_bytes": 43790492}, "explanation_from_pixels_4": {"description": "There are 3 caption contest tasks, described in the paper. 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diff --git a/newyorker_caption_contest.py b/newyorker_caption_contest.py
deleted file mode 100644
index e0b1b83c2bf5b2fd842bd0e1ce4966be27bf91a1..0000000000000000000000000000000000000000
--- a/newyorker_caption_contest.py
+++ /dev/null
@@ -1,402 +0,0 @@
-# coding=utf-8
-# Lint as: python3
-"""The Caption Contest benchmark."""
-
-
-import json
-import os
-import datasets
-import base64
-import pprint
-
-
-_CAPTION_CONTEST_TASKS_CITATION = """\
-@article{hessel2022androids,
-  title={Do Androids Laugh at Electric Sheep? Humor" Understanding" Benchmarks from The New Yorker Caption Contest},
-  author={Hessel, Jack and Marasovi{\'c}, Ana and Hwang, Jena D and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},
-  journal={arXiv preprint arXiv:2209.06293},
-  year={2022}
-}
-
-www.capcon.dev
-
-Our data contributions are:
-
-- The cartoon-level annotations;
-- The joke explanations;
-- and the framing of the tasks
-We release these data we contribute under CC-BY (see DATASET_LICENSE).
-
-If you find this data useful in your work, in addition to citing our contributions, please also cite the following, from which the cartoons/captions in our corpus are derived:
-
-@misc{newyorkernextmldataset,
-  author={Jain, Lalit  and Jamieson, Kevin and Mankoff, Robert and Nowak, Robert and Sievert, Scott},
-  title={The {N}ew {Y}orker Cartoon Caption Contest Dataset},
-  year={2020},
-  url={https://nextml.github.io/caption-contest-data/}
-}
-
-@inproceedings{radev-etal-2016-humor,
-  title = "Humor in Collective Discourse: Unsupervised Funniness Detection in The {New Yorker} Cartoon Caption Contest",
-  author = "Radev, Dragomir  and
-      Stent, Amanda  and
-      Tetreault, Joel  and
-      Pappu, Aasish  and
-      Iliakopoulou, Aikaterini  and
-      Chanfreau, Agustin  and
-      de Juan, Paloma  and
-      Vallmitjana, Jordi  and
-      Jaimes, Alejandro  and
-      Jha, Rahul  and
-      Mankoff, Robert",
-  booktitle = "LREC",
-  year = "2016",
-}
-
-@inproceedings{shahaf2015inside,
-  title={Inside jokes: Identifying humorous cartoon captions},
-  author={Shahaf, Dafna and Horvitz, Eric and Mankoff, Robert},
-  booktitle={KDD},
-  year={2015},
-}
-"""
-
-
-_CAPTION_CONTEST_DESCRIPTION = """\
-There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality
-of that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.
-"""
-
-_MATCHING_DESCRIPTION = """\
-You are given a cartoon and 5 captions. Only one of the captions was truly written about the cartoon. You must select it.
-"""
-
-_RANKING_DESCRIPTION = """\
-You are given a cartoon and 2 captions. One of the captions was selected by crowd voting or New Yorker editors as high quality. You must select it.
-"""
-
-_EXPLANATION_DESCRIPTION = """\
-You are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.
-"""
-
-
-_IMAGES_URL = "https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip"
-
-
-def _get_configs_crossvals():
-    cross_val_configs = []
-    for split_idx in [1,2,3,4]:
-        cur_split_configs = [
-            CaptionContestConfig(
-            name='matching_{}'.format(split_idx),
-                description=_MATCHING_DESCRIPTION,
-                features=[
-                    'image',
-                    'contest_number',
-                    'image_location',
-                    'image_description',
-                    'image_uncanny_description',
-                    'entities',
-                    'questions',
-                    'caption_choices',
-                    'from_description',
-                ],
-                label_classes=["A", "B", "C", "D", "E"],
-                data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_{}.zip'.format(split_idx),
-                url='www.capcon.dev',
-                citation=_CAPTION_CONTEST_TASKS_CITATION,
-            ),
-
-            CaptionContestConfig(
-                name='matching_from_pixels_{}'.format(split_idx),
-                description=_MATCHING_DESCRIPTION,
-                features=[
-                    'image',
-                    'contest_number',
-                    'caption_choices',
-                ],
-                label_classes=["A", "B", "C", "D", "E"],
-                data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels_{}.zip'.format(split_idx),
-                url='www.capcon.dev',
-                citation=_CAPTION_CONTEST_TASKS_CITATION,
-            ),
-
-            CaptionContestConfig(
-                name='ranking_{}'.format(split_idx),
-                description=_RANKING_DESCRIPTION,
-                features=[
-                    'image',
-                    'contest_number',
-                    'image_location',
-                    'image_description',
-                    'image_uncanny_description',
-                    'entities',
-                    'questions',
-                    'caption_choices',
-                    'from_description',
-                    'winner_source',
-                ],
-                
-                label_classes=["A", "B"],
-                data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_{}.zip'.format(split_idx),
-                url='www.capcon.dev',
-                citation=_CAPTION_CONTEST_TASKS_CITATION,
-            ),
-
-            CaptionContestConfig(
-                name='ranking_from_pixels_{}'.format(split_idx),
-                description=_RANKING_DESCRIPTION,
-                features=[
-                    'image',
-                    'contest_number',
-                    'caption_choices',
-                    'winner_source',
-                ],
-                label_classes=["A", "B"],
-                data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels_{}.zip'.format(split_idx),
-                url='www.capcon.dev',
-                citation=_CAPTION_CONTEST_TASKS_CITATION,
-            ),
-
-
-            CaptionContestConfig(
-                name='explanation_{}'.format(split_idx),
-                description=_EXPLANATION_DESCRIPTION,
-                features=[
-                    'image',
-                    'contest_number',
-                    'image_location',
-                    'image_description',
-                    'image_uncanny_description',
-                    'entities',
-                    'questions',
-                    'caption_choices',
-                    'from_description',
-                ],
-                label_classes=None,
-                data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_{}.zip'.format(split_idx),
-                url='www.capcon.dev',
-                citation=_CAPTION_CONTEST_TASKS_CITATION,
-            ),
-
-            CaptionContestConfig(
-                name='explanation_from_pixels_{}'.format(split_idx),
-                description=_EXPLANATION_DESCRIPTION,
-                features=[
-                    'image',
-                    'contest_number',
-                    'caption_choices',
-                ],
-                label_classes=None,
-                data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels_{}.zip'.format(split_idx),
-                url='www.capcon.dev',
-                citation=_CAPTION_CONTEST_TASKS_CITATION,
-            ),
-        ]
-        cross_val_configs.extend(cur_split_configs)
-    return cross_val_configs
-
-
-class CaptionContestConfig(datasets.BuilderConfig):
-    """BuilderConfig for Caption Contest."""
-
-    def __init__(self, features, data_url, citation, url, label_classes=None, **kwargs):
-        """BuilderConfig for Caption Contest.
-        Args:
-          features: `list[string]`, list of the features that will appear in the
-            feature dict. Should not include "label".
-          data_url: `string`, url to download the zip file from.
-          citation: `string`, citation for the data set.
-          url: `string`, url for information about the data set.
-          label_classes: `list[string]`, the list of classes for the label if the
-            label is present as a string. If not provided, there is no fixed label set.
-          **kwargs: keyword arguments forwarded to super.
-        """
-
-        super(CaptionContestConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
-        self.features = features
-        self.data_url = data_url
-        self.citation = citation
-        self.url = url
-        self.label_classes = label_classes
-
-
-class CaptionContest(datasets.GeneratorBasedBuilder):
-    """The CaptionContest benchmark."""
-
-    BUILDER_CONFIGS = [
-        CaptionContestConfig(
-            name='matching',
-            description=_MATCHING_DESCRIPTION,
-            features=[
-                'image',
-                'contest_number',
-                'image_location',
-                'image_description',
-                'image_uncanny_description',
-                'entities',
-                'questions',
-                'caption_choices',
-                'from_description',
-            ],
-            label_classes=["A", "B", "C", "D", "E"],
-            data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching.zip',
-            url='www.capcon.dev',
-            citation=_CAPTION_CONTEST_TASKS_CITATION,
-        ),
-
-        CaptionContestConfig(
-            name='matching_from_pixels',
-            description=_MATCHING_DESCRIPTION,
-            features=[
-                'image',
-                'contest_number',
-                'caption_choices',
-            ],
-            label_classes=["A", "B", "C", "D", "E"],
-            data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/matching_from_pixels.zip',
-            url='www.capcon.dev',
-            citation=_CAPTION_CONTEST_TASKS_CITATION,
-        ),
-
-        CaptionContestConfig(
-            name='ranking',
-            description=_RANKING_DESCRIPTION,
-            features=[
-                'image',
-                'contest_number',
-                'image_location',
-                'image_description',
-                'image_uncanny_description',
-                'entities',
-                'questions',
-                'caption_choices',
-                'from_description',
-                'winner_source',
-            ],
-            label_classes=["A", "B"],
-            data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking.zip',
-            url='www.capcon.dev',
-            citation=_CAPTION_CONTEST_TASKS_CITATION,
-        ),
-
-        CaptionContestConfig(
-            name='ranking_from_pixels',
-            description=_RANKING_DESCRIPTION,
-            features=[
-                'image',
-                'contest_number',
-                'caption_choices',
-                'winner_source',
-            ],
-            label_classes=["A", "B"],
-            data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels.zip',
-            url='www.capcon.dev',
-            citation=_CAPTION_CONTEST_TASKS_CITATION,
-        ),
-
-
-        CaptionContestConfig(
-            name='explanation',
-            description=_EXPLANATION_DESCRIPTION,
-            features=[
-                'image',
-                'contest_number',
-                'image_location',
-                'image_description',
-                'image_uncanny_description',
-                'entities',
-                'questions',
-                'caption_choices',
-                'from_description',
-            ],
-            label_classes=None,
-            data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation.zip',
-            url='www.capcon.dev',
-            citation=_CAPTION_CONTEST_TASKS_CITATION,
-        ),
-
-        CaptionContestConfig(
-            name='explanation_from_pixels',
-            description=_EXPLANATION_DESCRIPTION,
-            features=[
-                'image',
-                'contest_number',
-                'caption_choices',
-            ],
-            label_classes=None,
-            data_url='https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/explanation_from_pixels.zip',
-            url='www.capcon.dev',
-            citation=_CAPTION_CONTEST_TASKS_CITATION,
-        ),
-    ] + _get_configs_crossvals()
-    
-
-    def _info(self):
-        features = {feature: datasets.Value("string") for feature in self.config.features}
-        # things are strings except for contest_number, entities, questions, and caption choices (if not explanation)
-        features['contest_number'] = datasets.Value("int32")
-        if 'explanation' not in self.config.name:
-            features['caption_choices'] = datasets.features.Sequence(datasets.Value("string"))
-
-        if 'entities' in features:
-            features['entities'] = datasets.features.Sequence(datasets.Value("string"))
-
-        if 'questions' in features:
-            features['questions'] = datasets.features.Sequence(datasets.Value("string"))
-
-        if 'image' in features:
-            features['image'] = datasets.Image()
-            
-        features['label'] = datasets.Value("string")
-        features['n_tokens_label'] = datasets.Value("int32")
-        features['instance_id'] = datasets.Value("string")
-        
-        return datasets.DatasetInfo(
-            description=_CAPTION_CONTEST_DESCRIPTION + self.config.description,
-            features=datasets.Features(features),
-            homepage=self.config.url,
-            citation=self.config.citation
-        )
-
-    def _split_generators(self, dl_manager):
-        dl_dir = dl_manager.download_and_extract(self.config.data_url) or ""
-        self.images_dir = dl_manager.download_and_extract(_IMAGES_URL)
-        task_name = _get_task_name_from_data_url(self.config.data_url)
-        dl_dir = os.path.join(dl_dir, task_name)
-        
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "train.jsonl"),
-                    "split": datasets.Split.TRAIN,
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "val.jsonl"),
-                    "split": datasets.Split.VALIDATION,
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "test.jsonl"),
-                    "split": datasets.Split.TEST,
-                },
-            ),
-        ]
-
-    def _generate_examples(self, data_file, split):
-        with open(data_file, encoding="utf-8") as f:
-            for line in f:
-                row = json.loads(line)
-                with open(self.images_dir + "/all_contest_images/{}.jpeg".format(row['contest_number']), "rb") as image:
-                    row['image'] = {"path": self.images_dir + "/all_contest_images/{}.jpeg".format(row['contest_number']),
-                                    "bytes": image.read()}
-                yield row['instance_id'], row
-
-def _get_task_name_from_data_url(data_url):
-    return data_url.split("/")[-1].split(".")[0]
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