AI
PaperFormalizer: Author-in-the-Loop Autoformalization of Research Papers in Lean
Publication: cs.AI updates on arXiv.org
Author: Jiyuan Tan, Vasilis Syrgkanis, Jose Blanchet
Source published: 26/10/2026, 04:00:00 UTC
Briefing created: 26/10/2026, 06:33:36 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 26/10/2026, 04:03:24 UTC.
Briefings
PaperFormalizer is a Lean-based agentic pipeline that assists authors in identifying and fixing gaps in their research proofs. It transcribes LaTeX into a dependency graph, audits natural language statements for correctness, and formalizes them in Lean against Mathlib. The system stops at ambiguous points, presenting multiple repair proposals in natural language and TeX symbols for the author to accept, decline, or redirect. The output includes an annotated revised paper, a change report, and linked Lean code. The tool runs inside a coding agent and is available via GitHub and a dedicated website.
Key points
- PaperFormalizer uses a Lean-based agentic pipeline to transcribe LaTeX source into dependency graphs for auditing and formalization.
- The system stops at ambiguous statements, presenting multiple repair proposals in natural language and TeX symbols for author decision.
Context
This tool addresses the issue of small gaps in proofs or stated assumptions in research papers, aiming to make research that rests on mathematical proofs more robust by providing practical verification.
Limitations
Evidence is limited to the article's abstract and GitHub link; no user testing data, performance metrics, or specific implementation details are provided.
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