Leveraging Self-Motivated Learning to Enhance Language Model Reasoning Capabilities

By leveraging the inherent preference that a rationale leading to the correct answer is superior to one leading to an incorrect answer, this work proposes a self-motivated learning framework to enhance the reasoning capabilities of language models without relying on large models or extensive manual annotations.