AI RESEARCH
Explaining Too Much? Understanding How Large Language Model Reasoning Traces Influence Performance and Metacognition
arXiv CS.AI
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ArXi:2605.25856v1 Announce Type: cross Large Language Model interfaces are increasingly verbose, exposing intermediate reasoning traces alongside final answers. Traces are framed as transparency mechanisms, yet it is unclear how people use them to solve problems. We report a preregistered between-subjects study (N = 559) in which participants solved ten LSAT-style reasoning problems under one of three conditions: an Answer-only baseline, a Full-trace revealed before the answer, and a Summary-trace presented alongside the answer.