Humans Disengage, Reasoning Models Persist: Separating Difficulty Registration from Deliberation Allocation

תקציר מקורי באנגליתarXiv:2606.26502v4 Announce Type: replace Abstract: Large reasoning models (LRMs) tend to produce longer reasoning traces for problems on which humans also spend more time. This correspondence suggests a shared sensitivity to difficulty, yet difficult problems can invite both persistence and withdrawal. We distinguish difficulty registration, expressed in which problems elicit more deliberation, from the allocation of further work. We examine their relation in matched human and LRM data from visual abstraction, intuitive physics, and relational reasoning. On visual abstraction, model trace length tracks the human ordering of problems by duration. After item identity is controlled, successful human attempts last longer than failed attempts, while failed LRM attempts have longer traces than