GraphPKU/Case_or_Rule

exploring whether LLMs perform case-based or rule-based reasoning

Case-Based or Rule-Based: How Do Transformers Do the Math?

We explore whether LLMs perform case-based or rule-based reasoning in this work.

⭐ Official code for Case-Based or Rule-Based: How Do Transformers Do the Math?.

Requirements

Tested combination of python packages that can successfully complete the program is listed in requirements.txt. You can run the following script to install them.

pip install -r requirements.txt

Replication of Leave-Square-Out

To replicate our main experiments of Leaving-Square-Out, you need to download the GPT-2 or GPT-2 Medium models and put them in .\pretrained_models. Then, you can run the script train.py to fine-tune the pre-trained models.

Datasets

We provide the datasets for our main experiments in .\datasets. In each dataset, we provide a figure showing the train-test split data_split.png.

Llama

We adopt the FastChat Framework to finetune Llama-7B in ./llama.

Citation

If you want to use the code for your research, please cite our paper:

@misc{hu2024casebased,
      title={Case-Based or Rule-Based: How Do Transformers Do the Math?},
      author={Yi Hu and Xiaojuan Tang and Haotong Yang and Muhan Zhang},
      year={2024},
      eprint={2402.17709},
      archivePrefix={arXiv},
      primaryClass={cs.AI}
}