ICML'24 : Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought

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Set environment

Python 3.8 and above is recommended. After creating your python environment, you need to install the following packages.

pip install openai numpy sympy pandas

Set api key

Put your OpenAI api key in api_key.yaml.

Run

AQuA

cd aqua
python main.py <method> <begin_task_idx> <end_task_idx>
# for example
python main.py ctot 0 10

Game24

cd game24
python main.py <method> <begin_task_idx> <end_task_idx>
# for example
python main.py ctot 0 10

Sudoku

cd sudoku
python main.py <method> <begin_task_idx> <end_task_idx> <puzzle_size>
# for example
python main.py ctot 0 10 3

Others

There are other algorithms you can try by setting the 'method' parameter, including direct, cot(CoT), stot(SToT), c_stot(Comp-SToT), backtot(Back-SToT).

You can change the optional arguments: backend, n_generate_sample, n_select_sample, n_evaluate_time, max_round, n_cot_sample(for SC-CoT).

To find more information, you can:

python main.py --help

Citation

If you find this work is relevant with your research or applications, please feel free to cite our work!

@inproceedings{CToT,
  title={Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought},
  author={Zhang, Zhen-Yu and Han, Siwei and Yao, Huaxiu and Niu, Gang and Sugiyama, Masashi},
  booktitle={Proceedings of the 41st International Conference on Machine Learning (ICML 2020)},
  year={2024},
}