AI RESEARCH

When Is Thinking Enough? Early Exit via Sufficiency Assessment for Efficient Reasoning

arXiv CS.CL

ArXi:2604.06787v1 Announce Type: new Large reasoning models (LRMs) have achieved remarkable performance in complex reasoning tasks, driven by their powerful inference-time scaling capability. However, LRMs often suffer from overthinking, which results in substantial computational redundancy and significantly reduces efficiency. Early-exit methods aim to mitigate this issue by terminating reasoning once sufficient evidence has been generated, yet existing approaches mostly rely on handcrafted or empirical indicators that are unreliable and impractical. In this work, we