Self‑Assessment Training Boosts LLMs’ Ability to Recognize Limits
The authors demonstrate that current large language models routinely overestimate their competence, lacking the ability to decide when to solve or defer a task. By framing capability self‑assessment as a policy‑learning problem and applying reinforcement learning, they markedly improve LLMs’ self‑awareness without sacrificing original performance, with strong out‑of‑distribution generalization.