arXiv:2510.04520v2 Announce Type: replace Abstract: Accurate auto-formalization of theorem statements is essential for advancing automated discovery and verification of research-level mathematics, yet remains a major bottleneck for LLMs due to hallucinations, semantic mismatches, and their inability to synthesize new definitions. To tackle these issues, we present Aria (Agent for Retrieval and Iterative Autoformalization), a system for conjecture-level formalization in Lean that emulates human expert reasoning via a two-phase Graph-of-Thought process: recursively decomposing statements into a
The continuous advancements in large language models (LLMs) are pushing the boundaries of AI agents, making the auto-formalization of complex mathematical theorems a current frontier.
This development is crucial for automating high-level intellectual tasks, potentially accelerating mathematical discovery and verification beyond human capacity.
The ability of AI to accurately formalize complex theorems, overcoming previous limitations like hallucinations and semantic mismatches, significantly enhances its utility in scientific research.
- · AI research institutions
- · Mathematics community
- · Automated theorem provers
- · Lean formal verification system
- · Manual formalization efforts
Increased efficiency and accuracy in formalizing mathematical conjectures and theorems.
Acceleration of research and discovery in mathematics and related scientific fields.
The democratization of advanced mathematical verification, leading to new forms of scientific collaboration and education.
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Read at arXiv cs.AI