Cognitive Fatigue in Autoregressive Transformers: Formalization and Measurement 事件

Cognitive Fatigue in Autoregressive Transformers: Formalization and Measurement arXiv:2605.30981v1 Announce Type: new Abstract: Autoregressive language models frequently degrade during long-horizon generation, producing repetitive text, losing instruction adherence, and exhibiting unstable entropy. Despite the prevalence of these failures, practitioners lack online diagnostics to detect them in real-time as they occur. We formalize this degradation as cognitive fatigue, a measurable generation-