activity
20242026
collaborators

7 papers

cs.CL2026

Aligning Faithfulness for Theory-Scale Autoformalization

Yuming Feng, Tadd Mao, Dhruva Arekar +4

Autoformalization (AF) requires more than compilation: formal statements must preserve the meaning of their informal sources, a property known as faithfulness. An emerging frontier…

cs.AI2026

Does the Proof Prove It That Way? Faithful Formalization of Elements Proofs

Tadd Mao, Tianjun Zhong, Dhruva Arekar +5

In formal verification, both the autoformalization of statements and automated proof search have been studied extensively. While automated proof search can produce a formal proof t…

cs.AI2026

Theory-Level Autoformalization: From Isolated Statements to Unified Formal Knowledge Bases

Marcus J. Min, Mike He, Zhaoyu Li +5

Autoformalization translates informal natural language into formal, machine-verifiable languages. While most work focuses on individual statements, real formalization efforts are i…

cs.LG2026

Theory-Scale Auto-Formalization of Logics for Computer Science

Yuming Feng, Frederick Pu, One An +5

Auto-formalization is critical for scalable formal verification, but existing progress largely focuses on isolated statements, while theory-scale auto-formalization, which coherent…

cs.PL2025

A Case Study on the Effectiveness of LLMs in Verification with Proof Assistants

Barış Bayazıt, Yao Li, Xujie Si

Large language models (LLMs) can potentially help with verification using proof assistants by automating proofs. However, it is unclear how effective LLMs are in this task. In this…

cs.LG2025

LLM Library Learning Fails: A LEGO-Prover Case Study

Ian Berlot-Attwell, Frank Rudzicz, Xujie Si

Recent advancements in the coding, reasoning, and tool-using abilities of LLMs have spurred interest in library learning (i.e., online learning through the creation, storage, and r…

cs.LG2024

Library Learning Doesn't: The Curious Case of the Single-Use "Library"

Ian Berlot-Attwell, Frank Rudzicz, Xujie Si

Advances in Large Language Models (LLMs) have spurred a wave of LLM library learning systems for mathematical reasoning. These systems aim to learn a reusable library of tools, suc…