Ali Payani

DIVE: Unlocking Self-Improvement in Frozen Language Models Through Diversity-Driven Skill Evolution

DIVE is introduced, a diversity-driven framework that enables frozen LLMs to improve by evolving persistent natural-language skills from task experience and verifier feedback and consistently outperforms existing reasoning methods, prompt-optimization approaches, skill-development frameworks, and memory-based baselines...