Not All Negative Samples Are Equal: LLMs Learn Better from Plausible Reasoning

Zixiang Di, Jinyi Han, Shuo Zhang +8

Learning from negative samples holds great promise for improving Large Language Model (LLM) reasoning capability, yet existing methods treat all incorrect responses as equally info…