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Instructing Large Language Models to Identify and Ignore Irrelevant Conditions (NAACL 2024)

Introduction & Setup

This repository contains the code for the paper Instructing Large Language Models to Identify and Ignore Irrelevant Conditions (Accepted to NAACL Main 2024). I3C instructs LLMs to identify and ignore irrelevant conditions. I3C-Select selects the most confusing problems and their generated reasoning paths as demonstrations for few-shot learning.

image

  • Run I3C-Instruction-code/run.py to generate I3C instruction
python run.py --data_index 3
  • Run I3C-Select-code/run.py to generate the answer to the given math word problem
python run.py --data_index 3

Experimental Results

image

Citing I3C

@inproceedings{wu2024i3c,
  title={Instructing Large Language Models to Identify and Ignore Irrelevant Conditions},
  author={Zhenyu Wu and Chao Shen and Meng Jiang},
  booktitle={Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)},
  year={2024},
}

License

This project is licensed under the Apache-2.0 License.