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- ## Overview
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  **REAL-Prover** is a retrieval-augmented, stepwise large language model-based theorem prover for **Lean 4**. It is built on top of **Qwen2.5-Math-7B**, and fine-tuned using our custom pipeline and dataset to support formal reasoning in Lean. The model is integrated with a retrieval module (**Leansearch-PS**) that fetches relevant theorems from the Lean math library to enhance generation quality.
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  - Evaluations on both **ProofNet** and our proposed benchmark **FATE-M**
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- ## Associated Paper
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  **REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning**
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  [arXiv:2505.20613](https://arxiv.org/abs/2505.20613)
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- ## Running Experiments
 
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  **Repository**: [https://github.com/frenzymath/REAL-Prover](https://github.com/frenzymath/REAL-Prover)
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  ### Input Data Format
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  python -m experiment.run /path/to/config.toml
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  ```
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- ## Citation
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  ```bibtex
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  @article{shen2025realproverretrievalaugmentedlean,
 
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  </div>
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+ ## 1. Overview
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  **REAL-Prover** is a retrieval-augmented, stepwise large language model-based theorem prover for **Lean 4**. It is built on top of **Qwen2.5-Math-7B**, and fine-tuned using our custom pipeline and dataset to support formal reasoning in Lean. The model is integrated with a retrieval module (**Leansearch-PS**) that fetches relevant theorems from the Lean math library to enhance generation quality.
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  - Evaluations on both **ProofNet** and our proposed benchmark **FATE-M**
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+ ## 2. Associated Paper
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  **REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning**
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  [arXiv:2505.20613](https://arxiv.org/abs/2505.20613)
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+
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+ ## 3. Running Experiments
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  **Repository**: [https://github.com/frenzymath/REAL-Prover](https://github.com/frenzymath/REAL-Prover)
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  ### Input Data Format
 
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  python -m experiment.run /path/to/config.toml
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  ```
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+ ## 4. Citation
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  ```bibtex
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  @article{shen2025realproverretrievalaugmentedlean,