I Could've Asked That: Reformulating Unanswerable Questions

| Dataset | Paper |

Evaluate Your Models on the CouldAsk Dataset

Our code supports direct evaluation for models hosted on Hugging Face. To evaluate your model, first follow the instructions to upload your model to the Hugging Face model hub. Then run:

python run_baseline.py --model MODEL --dataset SUBSET

Please replace MODEL with your model ID, and SUBSET can be chosen from {bandit_qa, bbc, qa2, reddit, squad_v2, yelp}.

Reproduce experiments from the paper

To use models from OpenAI or Anthropic:

export OPENAI_API_KEY=[your openai api key]
export ANTHROPIC_API_KEY=[your anthropic api key]

The following script will reproduce all experiments in the paper:

for f in bandit_qa bbc qa2 reddit squad_v2 yelp
    do
        for model in gpt-3.5-turbo-0125 gpt-4-0613 meta-llama/Llama-2-7b-chat-hf mistralai/Mistral-7B-Instruct-v0.2 HuggingFaceH4/zephyr-7b-beta
            do
		python run_baseline.py --model $model --dataset $f
		python run_baseline.py --model $model --dataset $f --fewshot
		python run_baseline.py --model $model --dataset $f --cot
		python run_baseline.py --model $model --dataset $f --cot --fewshot
            done
    done

To evaluate the results produced from the experiments:

for f in out/*
    do
        echo $f
        python parse_baseline.py --dataset $f # compute detection scores
        python evaluate_new_question.py --dataset $f # compute question reformulation scores
    done

✍️ Citation

If you find our work helpful, please use the following citations.

@article{
    zhao2024couldask,
    title={I Could've Asked That: Reformulating Unanswerable Questions},
    author={Wenting Zhao, Ge Gao, Claire Cardie, Alexander M Rush},
    journal={arXiv preprint arXiv:2407.17469},
    year={2024}
}