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20242026
most citedFormal Theorem Proving by Rewarding LLMs to Decompose Proofs Hierarchically

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Trust the Critic More

Kaiyue Wen, Luke Bailey, Arvind Mahankali +1

Standard language model RL algorithms credit every token of a long rollout with the same advantage determined by the terminal reward. Actor-critic methods can provide finer-grained…

cs.LO2026

Pseudo-Formalization for Automatic Proof Verification

Slim Barkallah, Luke Bailey, Kaiyue Wen +2

Reliable verification of proofs remains a bottleneck for training and evaluating AI systems on hard mathematical reasoning. Fully formal proofs, in languages like Lean, are easy to…

cs.LG2026

Scaling Self-Play with Self-Guidance

Luke Bailey, Kaiyue Wen, Kefan Dong +2

LLM self-play algorithms are notable in that, in principle, nothing bounds their learning: a Conjecturer model creates problems for a Solver, and both improve together. However, in…

cs.LG2026

Divide-and-Conquer CoT: RL for Reducing Latency via Parallel Reasoning

Arvind Mahankali, Kaiyue Wen, Tengyu Ma

Long chain-of-thought reasoning (Long CoT) is now fundamental to state-of-the-art LLMs, especially in mathematical reasoning. However, LLM generation is highly sequential, and long…

cs.LG2025

STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving

Kefan Dong, Tengyu Ma

A fundamental challenge in formal theorem proving by LLMs is the lack of high-quality training data. Although reinforcement learning or expert iteration partially mitigates this is…

cs.LG2024★ 1 cited

Formal Theorem Proving by Rewarding LLMs to Decompose Proofs Hierarchically

Kefan Dong, Arvind Mahankali, Tengyu Ma

Mathematical theorem proving is an important testbed for large language models' deep and abstract reasoning capability. This paper focuses on improving LLMs' ability to write proof…