4 papers
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…
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…
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…
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…