Context anxiety causes frontier reasoning models to doubt their solutions despite capability; a study analyzes how misestimation of token difficulty affects performance.
Read the original at arxiv.org→arXiv:2607.21616v1 Announce Type: new Abstract: Conventional wisdom suggests that reasoning models fail when problems exceed their capabilities. However, we find that frontier reasoning models sometimes possess the...
Original headline: "Lost in Context: Addressing Context Anxiety in Large Language Models"
Coverage timeline
- Jul 28, 04:00 UTC arXiv cs.AI lead source Lost in Context: Addressing Context Anxiety in Large Language Models
- Jul 29, 04:00 UTC arXiv cs.CL Measuring and Improving Behavioral Consistency in Large Language Models through Fact-Heuristic-Emotion State Enforcement