评分 6 · 来源：cs.CL updates on arXiv.org · 发布于 2026-04-17
评分依据：Systematic analysis of reasoning failure modes, useful taxonomy for debugging LLM reasoning
arXiv:2604.14528v1 Announce Type: cross Abstract: Large Language Models (LLMs) achieve strong performance through extended inference-time deliberation, yet how their reasoning failures arise remains poorly understood. By analyzing model-generated reasoning trajectories, we find that errors are not uniformly distributed but often originate from a small number of early transition points, after which reasoning remains locally coherent but globally incorrect.