← all papers · overview

A Closer Look At The Self-verification Abilities Of Large Language Models In Logical Reasoning

Abstract

Logical reasoning has been an ongoing pursuit in the field of AI. Despite significant advancements made by large language models (LLMs), they still struggle with complex logical reasoning problems. To enhance reasoning performance, one promising direction is scalable oversight, which requires LLMs to identify their own errors and then improve by themselves. Various self-verification methods have b

Related papers

Ranked by semantic similarity — how closely each paper's abstract matches this one (100% = near-identical topic).