5 papers
Magenta: Closing the Loop Between Mathematical Reasoning and Lean Verification
Joshua Ong Jun Leang, Haonan Li, Zheng Zhao +6
Most of mathematical knowledge has been communicated through so-called informal use of mathematics and natural language. With large language models (LLMs) being highly adept in usi…
Pythagoras-Prover: Advancing Efficient Formal Proving via Augmented Lean Formalisation
Joshua Ong Jun Leang, Zheng Zhao, Mihaela Cătălina 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…
Can I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language Models
Joshua Ong Jun Leang, Yu Zhao, Mihaela Cătălina 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…
Right for the Right Reasons: Avoiding Reasoning Shortcuts via Prototypical Neurosymbolic AI
Luca Andolfi, Eleonora Giunchiglia
Neurosymbolic AI is growing in popularity thanks to its ability to combine neural perception and symbolic reasoning in end-to-end trainable models. However, recent findings reveal…
PiCSAR: Probabilistic Confidence Selection And Ranking for Reasoning Chains
Joshua Ong Jun Leang, Zheng Zhao, Aryo Pradipta Gema +7
Best-of-n sampling improves the accuracy of large language models (LLMs) and large reasoning models (LRMs) by generating multiple candidate solutions and selecting the one with the…