rautoformalizer_gtra_deepseek

<div align="center"> <h1 style="font-size: 1.5em;">[ICLR'25 Spotlight] Rethinking and Improving Autoformalization: Towards a Faithful Metric and a Dependency Retrieval-based Approach</h1> <div style="display: flex; justify-content: center; gap: 8px; flex-wrap: wrap;"> <a href="https://choosealicense.com/licenses/apache-2.0/"><img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg" alt="License: Apache 2.0"></a> <a href="https://github.com/leanprover-community/mathlib4"><img src="https://img.shields.io/badge/Lean-4-orange" alt="Lean 4"></a> <a href="https://github.com/Purewhite2019/rethinking_autoformalization"><img src="https://img.shields.io/badge/GitHub-%23121011.svg?logo=github&logoColor=white" alt="GitHub"></a> </div> <h2>Qi Liu, Xinhao Zheng, Xudong Lu, Qinxiang Cao*, Junchi Yan* (* indicates Correspondence author)</h2> <h2>Sch. of Computer Science & Sch. of Artificial Intelligence, Shanghai Jiao Tong University</h2> </div>

Please refer to the 📺GitHub repo and 📃Paper for more details.

📈 Performance

⚙️ Usage

w/o Dependency Retrieval

• 🤗purewhite42/rautoformalizer_nora_deepseek: w/o dependency retrieval, SFTed from 🤗deepseek-ai/deepseek-math-7b-base
• 🤗purewhite42/rautoformalizer_nora_internlm: w/o dependency retrieval, SFTed from 🤗internlm/internlm2-math-base-7b

python -m autoformalizer.autoformalize_vllm_passk \
    --port ... \    # Can be arbitrarily set (should avoid conflict)
    --trust-remote-code \
    --enable-prefix-caching \
    --model /path/to/model \
    --mathlib_root ... \ # Path to Mathlib 4 or path to Con(NF)
    --eval_set ... \    # {proofnet, connf}
    --working_root /path/to/output/results \
    --dataset_root ./data/ \
    --repl_root /path/to/repl \
    --try_num 8 \
    --num_concurrency 8 \
    --temperature 0.0;

RAutofromalizer (w/ Dependency Retrieval)

• 🤗purewhite42/rautoformalizer_ra_deepseek: w/ dependency retrieval (dependency_retriever_f), SFTed from 🤗deepseek-ai/deepseek-math-7b-base
• 🤗purewhite42/rautoformalizer_ra_internlm: w/ dependency retrieval (dependency_retriever_f), SFTed from 🤗internlm/internlm2-math-base-7b

python -m autoformalizer.autoformalize_vllm_w_ra_passk \
    --port ... \    # Can be arbitrarily set (should avoid conflict)
    --trust-remote-code \
    --enable-prefix-caching \
    --model /path/to/model \
    --retrieval_result_path /path/to/retrieval/result \
    --mathlib_root ... \ # Path to Mathlib 4 or path to Con(NF)
    --eval_set ... \    # {proofnet, connf}
    --working_root /path/to/output/results \
    --dataset_root ./data/ \
    --repl_root /path/to/repl \
    --try_num 8 \
    --num_concurrency 8 \
    --temperature 0.0;

Oracle RAutoformalizer (w/ Ground-truth Dependencies)

• 🤗purewhite42/rautoformalizer_gtra_deepseek: w/ oracle dependency retrieval, SFTed from 🤗deepseek-ai/deepseek-math-7b-base
• 🤗purewhite42/rautoformalizer_gtra_internlm: w/ oracle dependency retrieval, SFTed from 🤗internlm/internlm2-math-base-7b

python -m autoformalizer.autoformalize_vllm_w_gt_passk \
    --port ... \    # Can be arbitrarily set (should avoid conflict)
    --trust-remote-code \
    --enable-prefix-caching \
    --model /path/to/model \
    --mathlib_root ... \ # Path to Mathlib 4 or path to Con(NF)
    --eval_set ... \    # {proofnet, connf}
    --working_root /path/to/output/results \
    --dataset_root ./data/ \
    --repl_root /path/to/repl \
    --try_num 8 \
    --num_concurrency 8 \
    --temperature 0.0;

📚 Citation

If you find our work useful in your research, please cite

@inproceedings{
liu2025rethinking,
title={Rethinking and improving autoformalization: towards a faithful metric and a Dependency Retrieval-based approach},
author={Qi Liu and Xinhao Zheng and Xudong Lu and Qinxiang Cao and Junchi Yan},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025},
url={https://openreview.net/forum?id=hUb2At2DsQ}
}

License

This project is released under the Apache 2.0 license. Please see the LICENSE file for more information.

Contact

Feel free to discuss the paper/data/code with us through issues/emails!

• Qi Liu: [email protected]