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--- |
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configs: |
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- config_name: all |
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data_files: |
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- split: train |
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- path: commongen_hard_nohuman.json |
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license: apache-2.0 |
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task_categories: |
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- text-generation |
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language: |
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- en |
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pretty_name: CommonGen-Lite |
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size_categories: |
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- n<1K |
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--- |
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# CommonGen-Lite |
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Evaluating LLMs with [CommonGen](https://inklab.usc.edu/CommonGen/) using [CommonGen-lite](https://huggingface.co/datasets/allenai/commongen_lite) dataset (400 examples + 900 human references). |
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We use GPT-4 to evaluate the constrained text generation ability of LLMs. Please see more in our [paper](https://arxiv.org/abs/1911.03705). |
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Github: [https://github.com/allenai/CommonGen-Eval](https://github.com/allenai/CommonGen-Eval) |
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## Leaderboard |
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| model | len | cover | pos | win_tie | overall | |
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|----------------------------|-------|---------|-------|-----------|-----------| |
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| human | 12.84 | 99.00 | 98.11 | 100.00 | 97.13 | |
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| gpt-4-0613 | 14.13 | 97.44 | 91.78 | 50.44 | 45.11 | |
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| gpt-4-1106-preview | 14.90 | 96.33 | 90.11 | 50.78 | 44.08 | |
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| gpt-3.5-turbo | 12.76 | 92.11 | 83.00 | 49.78 | 38.06 | |
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| Yi-34b-chat | 13.45 | 80.11 | 75.11 | 39.44 | 23.73 | |
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| vicuna-13b-v1.5 | 15.02 | 85.89 | 79.56 | 27.44 | 18.75 | |
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| tulu-2-dpo-70b | 17.89 | 88.78 | 80.11 | 23.00 | 16.36 | |
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| Mixtral-8x7B-Instruct-v0.1 | 20.15 | 84.11 | 73.33 | 17.89 | 11.03 | |
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| Llama-2-7b-chat-hf | 16.06 | 88.56 | 76.44 | 15.44 | 10.45 | |
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| zephyr-7b-beta | 15.76 | 82.44 | 72.78 | 16.89 | 10.13 | |
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| Yi-6b-chat | 13.32 | 71.67 | 63.56 | 22.11 | 10.07 | |
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- **length**: the number of words on average in the generated sentences |
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- **cover**: the percentage of examples where all given concepts are covered by model outputs |
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- **PoS**: the percentage of examples where the part-of-speech (PoS) of ALL given concepts are correct in model outputs |
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- **win_tie**: the percentage of examples where GPT-4-turbo prefers the model outputs over the human-written references (or thinks they are equally good) |
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- **overall**: `cover%` x `pos%` x `win_tie%` |
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Link: [https://inklab.usc.edu/CommonGen/leaderboard.html](https://inklab.usc.edu/CommonGen/leaderboard.html) |
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To make your model on the leaderboard, please create an issue or PR to submit the inference script. I'll run the following evaluation script and update the leaderboard. |
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You will not need to run the evaluation script yourself (the human references are hidden to avoid data leakage). |
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## Prompts |
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<details> |
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<summary>Instruction Prompt Template (2-shots prompting)</summary> |
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```markdown |
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# Instruction |
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Given several concepts (i.e., nouns or verbs), write a short and simple sentence that contains *all* the required words. |
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The sentence should describe a common scene in daily life, and the concepts should be used in a natural way. |
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# Examples |
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## Example 1 |
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- Concepts: "dog(noun), frisbee(noun), catch(verb), throw(verb)" |
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- Sentence: The dog catches the frisbee when the boy throws it into the air. |
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## Example 2 |
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- Concepts: "apple(noun), place(verb), tree(noun), pick(verb)" |
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- Sentence: A girl picks some apples from a tree and places them into her basket. |
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# Your Task |
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- Concepts: "{$concept_list}" |
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- Sentence: |
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``` |
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</details> |
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<details> |
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<summary>Evaluation Prompt Template (Pairwise Comparison)</summary> |
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```markdown |
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# Data |
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Given several concepts (i.e., nouns or verbs), we ask models to write a short and simple sentence that contains *all* the required words. |
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The sentence should describe a common scene in daily life, and the concepts should be used in a natural way. |
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Concepts: "{$concept_list}" |
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Model A: "{$candidate_A}" |
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Model B: "{$candidate_B}" |
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# Your Task |
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Your task is to choose a better sentence from the two candidates. Decide which model's sentence is better in terms of the naturalness and commonness of the scenes they describe. |
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## Rules: |
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- A better sentence should describe a common scene in daily life, and all concepts should be used in a natural way. |
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- You should prefer sentences that use all given concepts with correct part-of-speech tags. |
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- A simpler and shorter sentence is preferred if it describes the same scene as the other sentence. |
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- If you think both sentences are equally good or bad, please choose "tie". |
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Now, please output your choice ("A" or "B" or "tie"). |
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Your choice: |
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``` |
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</details> |
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## Case studies |
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Here are some examples of the generated sentences from the models. |
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<details> |
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<summary> Example 1 </summary> |
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- **Concepts**: `['demonstrate_V', 'machine_N', 'sew_V', 'use_V']` |
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- **Human Reference**: `She used the sewing machine to demonstrate how well she could sew.` |
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- **Mixtral-8x7B-Instruct-v0.1**: ` During the fashion design class, the teacher demonstrates how to use the sewing machine to create a stylish outfit.` |
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--> ```Versus=lose; Cover=False; PoS=False; Len=20``` |
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- **Yi-34b-chat**: `The tailor demonstrates how to use the sewing machine.` |
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--> ```Versus=win; Cover=False; PoS=False; Len=9``` |
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- **Yi-6b-chat**: `The machine demonstrates how to sew a useful item.` |
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--> ```Versus=lose; Cover=False; PoS=False; Len=9``` |
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- **Llama-2-7b-chat-hf**: `The teacher demonstrates how to use the sewing machine to sew a new dress, which the student will use to create a beautiful outfit for the school play.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=28``` |
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- **zephyr-7b-beta**: `The tailor demonstrates how to use the sewing machine to create garments by allowing the customer to try it out themselves.` |
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--> ```Versus=lose; Cover=False; PoS=False; Len=21``` |
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- **tulu-2-dpo-70b**: `A woman demonstrates how to use a machine to sew, showing the audience step by step.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=16``` |
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- **vicuna-13b-v1.5**: ` The tailor demonstrates how to use the sewing machine to make a dress.` |
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--> ```Versus=lose; Cover=False; PoS=False; Len=14``` |
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- **gpt-3.5-turbo**: `The tailor uses the sewing machine to demonstrate how to sew a straight line.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=14``` |
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- **gpt-4-0613**: `The instructor demonstrates how to use the sewing machine by sewing a piece of fabric.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=15``` |
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- **gpt-4-1106-preview**: `The tailor demonstrates how to use the sewing machine by making a small pouch.` |
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--> ```Versus=win; Cover=False; PoS=False; Len=14``` |
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</details> |
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<details> |
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<summary> Example 2 </summary> |
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- **Concepts**: `['car_N', 'drive_V', 'road_N', 'water_N']` |
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- **Human Reference**: `A man drives the car slowly because there is water on the road` |
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- **Mixtral-8x7B-Instruct-v0.1**: ` During the road trip, the family takes breaks to drink water next to the car driving on the open road.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=21``` |
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- **Yi-34b-chat**: `The car drives down the road splashing water from the puddles.` |
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--> ```Versus=win; Cover=True; PoS=True; Len=11``` |
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- **Yi-6b-chat**: `The car drives along the road, avoiding the puddle of water.` |
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--> ```Versus=win; Cover=True; PoS=True; Len=11``` |
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- **Llama-2-7b-chat-hf**: `The driver drives the car along the road, feeling the water splashing against the tires.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=15``` |
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- **zephyr-7b-beta**: `The driver takes the car along the road until they reach a place with water, where they cannot drive anymore.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=20``` |
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- **tulu-2-dpo-70b**: `A person drives their car on the road next to a river, where the water is flowing smoothly.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=18``` |
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- **vicuna-13b-v1.5**: ` The car drives on the road by the water.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=10``` |
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- **gpt-3.5-turbo**: `I drive my car on the road next to the water.` |
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--> ```Versus=win; Cover=True; PoS=True; Len=11``` |
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- **gpt-4-0613**: `The man drives his car on the road that runs alongside the sparkling water.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=14``` |
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- **gpt-4-1106-preview**: `The car drives smoothly on the wet road, splashing water as it goes.` |
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--> ```Versus=win; Cover=True; PoS=True; Len=13``` |
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</details> |
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<details> |
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<summary> Example 3 </summary> |
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- **Concepts**: `['ceiling_N', 'climb_V', 'gym_N', 'rope_N', 'suspend_V']` |
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- **Human Reference**: `The boys climbed the rope suspended from the gym ceiling.` |
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- **Mixtral-8x7B-Instruct-v0.1**: ` During gym class, the students take turns climbing the suspended rope while the others cheer from below, careful not to hit their heads on the ceiling.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=27``` |
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- **Yi-34b-chat**: `The gymnast climbs the rope and suspends from the ceiling of the gym.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=13``` |
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- **Yi-6b-chat**: `The climber suspends themselves on the rope as they climb the gym's ceiling.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=13``` |
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- **Llama-2-7b-chat-hf**: `The gym teacher suspends herself from the ceiling using a rope while climbing to reach the high bar for a workout.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=21``` |
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- **zephyr-7b-beta**: `Gymnasts suspend themselves from the ceiling by climbing on the ropes in the gym.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=14``` |
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- **tulu-2-dpo-70b**: `In the gym, an athlete climbs a rope suspended from the ceiling to improve their physical fitness.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=17``` |
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- **vicuna-13b-v1.5**: ` In the gym, she climbs up to the ceiling using a rope that is suspended from the top.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=19``` |
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- **gpt-3.5-turbo**: `In the gym, the athlete climbs the rope and suspends himself from the ceiling.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=14``` |
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- **gpt-4-0613**: `In the gym, a man climbs a rope that is suspended from the ceiling.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=14``` |
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- **gpt-4-1106-preview**: `In the gym, the rope is suspended from the ceiling for athletes to climb during their workout.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=17``` |
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</details> |
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<details> |
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<summary> Example 4 </summary> |
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- **Concepts**: `['hat_N', 'knit_V', 'pile_N', 'rock_N', 'sit_V']` |
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- **Human Reference**: `The woman sat on a pile of rocks and knitted a hat.` |
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- **Mixtral-8x7B-Instruct-v0.1**: ` During her break, a woman sits on a rock and starts to knit a pile of hats to sell at the local market.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=24``` |
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- **Yi-34b-chat**: `The knitted hat sat on a pile of rocks.` |
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--> ```Versus=lose; Cover=False; PoS=False; Len=9``` |
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- **Yi-6b-chat**: `The woman knits a cozy hat while sitting on a rock, placing the pile of rocks around her.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=18``` |
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- **Llama-2-7b-chat-hf**: `The old man sits on a rock and knits a new hat while piling up the ones he already has, enjoying the peaceful atmosphere.` |
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--> ```Versus=lose; Cover=True; PoS=False; Len=24``` |
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- **zephyr-7b-beta**: `A woman sits on a rock and knits a hat from a pile of yarn.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=15``` |
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- **tulu-2-dpo-70b**: `An elderly woman knits a colorful hat while sitting on a pile of rocks, enjoying the peaceful scenery around her.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=20``` |
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- **vicuna-13b-v1.5**: ` The old man sits on a rock and knits a hat in a pile of yarn.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=17``` |
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- **gpt-3.5-turbo**: `The old man sits on a rock, wearing a knitted hat, while a pile of leaves gathers around him.` |
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--> ```Versus=lose; Cover=False; PoS=False; Len=19``` |
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- **gpt-4-0613**: `The woman sits on a rock, knitting a hat, with a pile of yarn beside her.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=16``` |
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- **gpt-4-1106-preview**: `She sits on a rock, knitting a hat, and places the finished ones in a colorful pile beside her.` |
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--> ```Versus=lose; Cover=True; PoS=True; Len=19``` |
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</details> |
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## Links |
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- Contact: [Bill Yuchen Lin](https://yuchenlin.xyz/) |
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- Project website: [https://inklab.usc.edu/CommonGen/](https://inklab.usc.edu/CommonGen/) |
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- HuggingFace Dataset: [CommonGen-lite](https://huggingface.co/datasets/allenai/commongen_lite) |
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## Citation |
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```bibtex |
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@inproceedings{lin-etal-2020-commongen, |
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title = "{C}ommon{G}en: A Constrained Text Generation Challenge for Generative Commonsense Reasoning", |
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author = "Lin, Bill Yuchen and |
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Zhou, Wangchunshu and |
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Shen, Ming and |
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Zhou, Pei and |
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Bhagavatula, Chandra and |
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Choi, Yejin and |
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Ren, Xiang", |
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booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020", |
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month = nov, |
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year = "2020", |
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address = "Online", |
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publisher = "Association for Computational Linguistics", |
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url = "https://www.aclweb.org/anthology/2020.findings-emnlp.165", |
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pages = "1823--1840", |
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} |
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``` |
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