
Sign up to save your podcasts
Or


Title: Logic-Regularized Verifier Elicits Reasoning from LLMs
Source: http://arxiv.org/abs/2605.05893v1
Summary:
This work presents a novel reasoning framework that uses logical consistency rules to regularize unsupervised verifiers, eliminating the need for expensive supervised datasets. By treating verification as a binary latent variable problem, it achieves performance comparable to supervised models in eliciting complex reasoning from off-the-shelf LLMs.
By Yun WuTitle: Logic-Regularized Verifier Elicits Reasoning from LLMs
Source: http://arxiv.org/abs/2605.05893v1
Summary:
This work presents a novel reasoning framework that uses logical consistency rules to regularize unsupervised verifiers, eliminating the need for expensive supervised datasets. By treating verification as a binary latent variable problem, it achieves performance comparable to supervised models in eliciting complex reasoning from off-the-shelf LLMs.