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Reading Too Much Into It? Interpretive Preferences and Commitment in LLM Mentalisation under Ambiguity

Stephanie Fong, Yiwen Jiang, Qingyang Xu, Zimu Wang, Yaling Shen, Xiangyu Zhao, Jiahe Liu, Yinghao Zhang, Vincent Lee, Dominic Edmund Dwyer · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.28105 · cited by 0 works (OpenAlex) · open-access PDF

Japanese

大規模な言語モデル(LLMs)は、ますます人々の間でのアドバイスに使用され、潜在的にユーザーが曖昧な社会的出会いを解釈する方法を形作ります。既存のTheory of Mind評価は通常、事前定義された回答に依存し、不確実性の研究は、心理的な困難の下でLLMの好ましい説明と自信を無視しています。これらのギャップを解決するために、私たちはMentalLoomを導入し、LLMの心理学の新しい評価は、604の曖昧な社会的エピソード、マッチされたうつ病と社会的不安の暴露、および変化しない出来事の証拠を含む4回の対話を含みます。8 LLMsを通して、開示は全体的により多くのネガティブな

Machine translation (Meta M2M100); the English original follows.

Abstract

Large Language Models (LLMs) are increasingly used for interpersonal advice, potentially shaping how users interpret ambiguous social encounters. Existing Theory of Mind evaluations typically rely on predefined answers, while uncertainty research overlooks LLMs' preferred explanations and confidence under psychological distress. To address these gaps, we introduce MentalLoom, a novel evaluation of LLM mentalisation comprising 604 ambiguous social episodes, matched depression and social anxiety disclosures, and four-turn dialogues with unchanged event evidence. Across eight LLMs, disclosures initially elicited more negative explanations overall but more positive narrator-directed interpretations. Scripted repeated questioning showed greater emotional support, stronger positive narrator-directed endorsement, and higher certainty without new event evidence. These findings show that user context can reshape interpretive preferences and commitment while the underlying ambiguity remains unresolved.

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Topics: Ambiguity, Psychology, Certainty, Social psychology, Context (archaeology), Reading (process)

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