Fan Yang

LLM agents can learn complex tasks more efficiently by adaptively injecting skills only when their utility is confirmed through outcome-aware likelihood comparisons on existing data, bypassing expensive environment rollouts.

Robots can't truly improve themselves yet; current systems lack the crucial ability to recursively refine their own learning processes based on physical experience.