Early Stopping Chain-of-thoughts in Large Language Models

ArXi:2509.14004v2 Announce Type: replace Reasoning large language models (LLMs) have nstrated superior capacities in solving complicated problems by generating long chain-of-thoughts (CoT), but such a lengthy CoT incurs high inference costs. Previous methods on inference-stage efficient reasoning either require white-box models to monitor the reasoning process or are not reliable through direct prompting. In response, we