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 ## What StatProver Does
 
-StatProver provides a structured workflow for automated proof generation and self-correction, helping users transform a statistical proposition or source document into a complete LaTeX proof. Built on the comprehensive statistical reasoning benchmark **[StatEval](https://stateval.github.io/)**, StatProver retrieves relevant references to refine proof skeletons and performs self-correction by learning from the strategies and details of similar theoretical proofs.
+StatProver provides a structured workflow for automated proof generation and self-correction, helping users transform a statistical proposition or source document into a complete LaTeX proof. Built on the comprehensive statistical reasoning benchmark **[StatEval](https://statai-lab.github.io/StatEval.github.io/)**, StatProver retrieves relevant references to refine proof skeletons and performs self-correction by learning from the strategies and details of similar theoretical proofs.
 
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 **Contribution 1. Retrieval-Driven Framework Refinement**
 
-StatProver retrieves reference cases from a database of **40,366** research-level statistical problems drawn from **[StatEval](https://stateval.github.io/)**. Through similarity-based retrieval and framework verification, the system refines the initial proof skeleton and improves the global structure of the derivation.
+StatProver retrieves reference cases from a database of **40,366** research-level statistical problems drawn from **[StatEval](https://statai-lab.github.io/StatEval.github.io/)**. Through similarity-based retrieval and framework verification, the system refines the initial proof skeleton and improves the global structure of the derivation.
 
 **Contribution 2. Data-Driven Snippet-Level Self-Correction**
 
-StatProver also uses a large empirical fault repository containing over **80,000** error snippets, constructed from LLM failure trajectories on **[StatEval’s](https://stateval.github.io/)** research-level data. This repository supports fine-grained diagnosis and targeted correction, allowing the system to identify subtle logical gaps and proof errors beyond standard self-reflection.
+StatProver also uses a large empirical fault repository containing over **80,000** error snippets, constructed from LLM failure trajectories on **[StatEval’s](https://statai-lab.github.io/StatEval.github.io/)** research-level data. This repository supports fine-grained diagnosis and targeted correction, allowing the system to identify subtle logical gaps and proof errors beyond standard self-reflection.
 
 **Contribution 3. Interactive Proof Assistant Platform**
 
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 * **[StatAI Lab](https://statai-lab.github.io/)**: [statai@163.com](mailto:statai@163.com)
 * **[Prof. Fan Zhou](https://mlzxzhou.github.io/)** (Project Leader): [zhoufan@mail.shufe.edu.cn](mailto:zhoufan@mail.shufe.edu.cn)
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