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PANDA

This repo contains the codes for our work 🐼PANDA: Preference Adaptation for Enhancing Domain-Specific Abilities of LLMs.

The required package can be installed by running the following command.

pip install -r requirements.txt

ScienceWorld

Firstly, switch to the ScienceWorld workspace:

cd ScienceWorld
  1. To directly run experiments with PANDA (You can also run PANDA from scratch by starting from step1).
./run_eval_react_panda.sh
./run_eval_reflexion_panda.sh
./run_eval_saycan_panda.sh
  1. Step1: Gather expert trials to construct preferences data.
./gather_trials.sh
  1. Step2: PANDA-Learning from the expert preferences.
./panda_learning.sh
  1. Step3: Test with PANDA-Insight:
./run_eval_react_panda.sh
./run_eval_reflexion_panda.sh
./run_eval_saycan_panda.sh

TweetEval

Firstly, switch to the ScienceWorld workspace:

cd TweetEval

  1. Step0: Download datasets file from cardifnlp/tweeteval and put it in the dataset folder and the expert models from cardifnlp/models and put it in the models folder.

  2. Step1: Gather expert trials to construct preferences data.

./gather_trials.sh
  1. Step2: PANDA-Learning from the expert preferences.
./panda_learning.sh
  1. Step3: Test with PANDA-Insight:
./eval_gpt.sh
./eval_gpt_cot.sh

Acknowledgement

Our codes for scienceworld are adapted from yuchenlin/SwiftSage. Thanks for their kind open-sourced code.

Citation

If you find our project helpful to your research, please consider citing:

@inproceedings{liu2024panda,
  title={PANDA: Preference Adaptation for Enhancing Domain-Specific Abilities of LLMs},
  author={Liu, An and Yang, Zonghan and Zhang, Zhenhe and Hu, Qingyuan and Li, Peng and Yan, Ming and Zhang, Ji and Huang, Fei and Liu, Yang},
  booktitle={Findings of the Association for Computational Linguistics: ACL 2024},
  year={2024}
}