[NeurIPS 2025] A Theoretical Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning
Official Repository for NeurIPS 2025 Paper: "A Theoretical Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning"
We provide two ways to create the Python environment for this repository. Please choose one of the following methods:
python -m venv rpc
source rpc/bin/activate
pip install -r requirements.txt conda create -n rpc python=3.9
conda activate rpc
pip install -r requirements.txtRun evaluation with specific parameters:
python main.py --dataset MathOdyssey --model InternLM2-Math-Plus-7B --method RPC --K 128Parameters:
--dataset: Choose fromMATH,MathOdyssey,AIME,OlympiadBench--model: Choose fromDeepseek-Math-RL-7B,InternLM2-Math-Plus-1.8B,InternLM2-Math-Plus-7B--method: Choose fromPPL(Perplexity),SC(Self-Consistency),RPC(our method)--K: Number of reasoning paths to sample (128forMathOdyssey,AIME,OlympiadBench, and64forMATH)
Run comprehensive evaluation across multiple settings:
bash all_exps.shThis will evaluate all method-dataset-model combinations and save results to results.txt.
- If you cannot download data from Hugging Face directly, please use Hugging Mirror instead.
- It may take some time to generate the cache for checking answer equality when running each dataset for the first time.
@inproceedings{zhou24theoretical,
author = {Zhou, Zhi and Tan, Yuhao and Li, Zenan and Yao, Yuan and Guo, Lan-Zhe and Li, Yu-Feng and Ma, Xiaoxing},
title = {A Theorecial Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning},
booktitle = {Advances in Neural Information Processing Systems},
year = {2025},
}