Datasets:
Modalities:
Text
Size:
10K - 100K
Tags:
Multimodal benchmark
Vision-Language Models
Compositionality
Localism-aware compositionality
Multimodal knowledge editing
License:
Upload dataset (incl. keyword dicts)
Browse files- README.md +45 -0
- data/test_keyword_dict.parquet +3 -0
- data/train_keyword_dict.parquet +3 -0
README.md
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- Compositionality
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- Localism-aware compositionality
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- Multimodal knowledge editing
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---
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# LACE-Bench: Localism-Aware Compositionality Evaluation Benchmark for Vision-Language Models
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| `region_ids` | list[string] | IDs of the atomic regions involved in this relational group (e.g. `["2358647_0", "2358647_1"]`) |
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## Citation
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```bibtex
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- Compositionality
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- Localism-aware compositionality
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- Multimodal knowledge editing
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/lace_train.parquet
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- split: test
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path: data/lace_test.parquet
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- config_name: keyword_dict
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data_files:
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- split: train
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path: data/train_keyword_dict.parquet
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- split: test
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path: data/test_keyword_dict.parquet
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---
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# LACE-Bench: Localism-Aware Compositionality Evaluation Benchmark for Vision-Language Models
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| `region_ids` | list[string] | IDs of the atomic regions involved in this relational group (e.g. `["2358647_0", "2358647_1"]`) |
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## `keyword_dict` Config
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In addition to the per-image records (`default` config), the dataset ships a `keyword_dict` config that maps each WordNet synset ID to the list of surface phrases observed for that concept across the corresponding split's region captions. These dictionaries are useful for keyword-based lookup, counterfactual phrase matching, and lexical normalization of mentions.
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**Files**
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- `data/train_keyword_dict.parquet`
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- `data/test_keyword_dict.parquet`
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**Schema**
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| Field | Type | Description |
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|---|---|---|
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| `synset_id` | string | WordNet synset identifier (e.g. `tree.n.01`), matching `keywords[].synset_id` in the `default` config |
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| `phrases` | list[string] | All distinct surface phrases (synonyms, plural forms, modifier-noun variants, casing variants) observed for the synset in that split |
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**Example rows**
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| `synset_id` | `phrases` |
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|---|---|
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| `leaf.n.01` | `["leaves", "foliage", "leaf", "banana leaf", "dried leaves", "green leaves", ...]` |
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| `tree.n.01` | `["tree", "trunk", "evergreen tree", "pine trees", "fir tree", ...]` |
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| `bus.n.01` | `["bus", "city bus", "double decker bus", "motorbus", "coach", ...]` |
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**Loading**
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```python
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from datasets import load_dataset
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ds = load_dataset("lacebench/LACE-Bench", "keyword_dict")
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```
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## Citation
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```bibtex
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data/test_keyword_dict.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:1dea3544ab2bfe479181ce8ff64676eed6aa4910d9775ce0a86d652ee0e5d99c
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size 158525
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data/train_keyword_dict.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:c0b1ca3e681b04bd2ba790b9a5c799aca352eda2960e40d6bdf7d6846f96a079
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size 287982
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