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reading correctly credits the study to Xiulin Yang, Sirisha Gudavalli and Jennifer Hu. Findings and interpretations are framed as the authors' reports and suggestions, not as established fact or EM opinion.","excerpt":"Authors:Xiulin Yang, Sirisha Gudavalli, Jennifer Hu"},{"dimension":"summary","status":"pass","explanation":"The title matches the source. The summary explains The Mind's key constraint, spells out CUAs and LLMs, and defines the Bayesian strategy in plain terms. It keeps the authors' inference-versus-adaptation contrast and their hedged cognitive claim. The game's goal is not described, but the abstract does not give it either, and the central idea is still clear. The question is open and follows from the reported adaptation gap.","excerpt":"none of the tested models seem to efficiently adapt their behaviors to their partners' over the course of the game"},{"dimension":"date","status":"pass","explanation":"The originalPublished date of 2026-11-10 matches the arXiv v1 submission date. The later feed date (2026-11-13) was correctly not used.","excerpt":"[Submitted on 10 Nov 2026]"},{"dimension":"support","status":"pass","explanation":"Each claim matches the abstract and keeps its hedging, including 'seem to' and 'may emerge'. The practical challenge mirrors the authors' wording about learning to interpret and adapt to implicit signals. The limitations correctly note that the evidence is an abstract only and that generalization is unknown. No benefits, costs or forecasts are invented.","excerpt":"our study highlights new challenges for AI systems to coordinate efficiently with other agents by learning to interpret and adapt to their implicit signals in dynamic settings"},{"dimension":"media","status":"pass","explanation":"The selected media is the verified direct arXiv abstract page for this paper, which is the most direct way to reach the source.","excerpt":null}],"createdAt":"2026-11-13T11:33:33.457Z","model":"anthropic/claude-opus-5.5"}],"correctionUrl":"https://escapemeridian.com/corrections/"}