Multi-agent AI system formalizes entire 500-page graduate algebraic combinatorics textbook into Lean, creating 130K lines of code in one week at human-expert cost.
At which training stage does code data help llms reasoning?, 2023.https://arxiv.org/abs/2309.16298
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Controlled experiments show structured reasoning traces and higher-density math-domain samples improve mathematical reasoning more than pure executable code, with internal routing patterns reflecting these data effects.
A review of 114 studies creates taxonomies for code and data quality issues, formalizes 18 propagation mechanisms from training data defects to LLM-generated code defects, and synthesizes detection and mitigation techniques.
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Automatic Textbook Formalization
Multi-agent AI system formalizes entire 500-page graduate algebraic combinatorics textbook into Lean, creating 130K lines of code in one week at human-expert cost.
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What Really Improves Mathematical Reasoning: Structured Reasoning Signals Beyond Pure Code
Controlled experiments show structured reasoning traces and higher-density math-domain samples improve mathematical reasoning more than pure executable code, with internal routing patterns reflecting these data effects.
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Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code
A review of 114 studies creates taxonomies for code and data quality issues, formalizes 18 propagation mechanisms from training data defects to LLM-generated code defects, and synthesizes detection and mitigation techniques.