Self-Improving LLMs Framework

Stony Brook researchers published a survey organizing self-improving LLMs into a closed-loop lifecycle (data acquisition, selection, optimization, inference refinement). This provides a blueprint for autonomous model improvement, with risks of self-reinforcing errors noted.