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complementaryexpl's Introduction

ComplementaryExpl

Code for the MMR exemplar-selection strategy described in the paper Complementary Explanations for Effective In-Context Learning (ACL Findings, 2023).

Setup

  • python==3.8
  • requirements: pip install -r requirements.txt
  • Set OPENAI KEY: export KEY=yourkey

Experiments

Preparation: sh prepare_data.sh

Example selection exeperiments on GSM:

sh exp_scripts/gsm.sh

Example selection exeperiments ECQA:

sh exp_scripts/ecqa.sh

Example selection exeperiments ESNLI:

sh exp_scripts/esnli.sh

Citation

@InProceedings{Ye-Et-Al:2023:Complementary,
  title = {Complementary Explanations for Effective In-Context Learning},
  author = {Xi Ye and Srinivasan Iyer and Asli Celikyilmaz and Ves Stoyanov and Greg Durrett and Ramakanth Pasunuru},
  booktitle = {Findings of ACL},
  year = {2023},
}

complementaryexpl's People

Contributors

xiye17 avatar

Stargazers

Anirudh Som avatar Li Moxin avatar

Watchers

Ramakanth Pasunuru avatar avatar

Forkers

manofwhat

complementaryexpl's Issues

Is there an issue with the provided dataset?

Dear Author,

Thank you very much for open-sourcing your code and dataset. I encountered an issue with a missing cache file while running the GSM experiment. Your code requires reading BERT scores between examples from 'misc/gsm--tr0-512-dv0-500--bertscoreapi-question--scores.json'. However, the provided cache folder does not contain this score file. Upon checking the provided files, I found that they contain results with keys dict_keys(['text', 'index', 'finish_reason', 'prompt', 'completion_offset']), where prompt includes the final example list input to the model. Therefore, I am curious if there might be some issues with the dataset. I look forward to your response.

Best regards

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