10 papers
AoA: Theorem Proving Agent over Abstract Syntax Tree of Redesigned Language
Qiyuan Xu, Joshua Ong Jun Leang, Renxi Wang +4
Interactive theorem proving (ITP) underpins program verification and formalized mathematics, but its manual effort limits scalability. LLM-based proof agents promise to ease this e…
PiCSAR: Probabilistic Confidence Selection And Ranking for Reasoning Chains
Joshua Ong Jun Leang, Zheng Zhao, Aryo Pradipta Gema +7
The paper proposes PiCSAR, a training-free scoring method that uses the joint log-likelihood of reasoning steps and final answer to select the most reliable reasoning chain from mu…
OpenSIR: Open-Ended Self-Improving Reasoner
Wai-Chung Kwan, Joshua Ong Jun Leang, Pavlos Vougiouklis +3
Recent advances in large language model (LLM) reasoning through reinforcement learning rely on annotated datasets for verifiable rewards, which may limit models' ability to surpass…
Pythagoras-Prover: Advancing Efficient Formal Proving via Augmented Lean Formalisation
Joshua Ong Jun Leang, Zheng Zhao, Mihaela CÄtÄlina Stoian +5
Modern Lean theorem provers achieve strong performance only with substantial training and inference compute, driven in part by scarce verified proof data and the long reasoning tra…
SCOPE: Self-Play via Co-Evolving Policies for Open-Ended Tasks
Wai-Chung Kwan, Aryo Pradipta Gema, Joshua Ong Jun Leang +1
Self-play can train language models without external supervision. However, existing methods require rule-checkable answers, leaving open-ended tasks dependent on curated prompts or…
Can I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language Models
Joshua Ong Jun Leang, Yu Zhao, Mihaela CÄtÄlina Stoian +3
While plan-and-infill decoding in Masked Diffusion Models (MDMs) shows promise for mathematical and code reasoning, performance remains highly sensitive to slot infilling order, of…