arXiv: cs.AI preprintsInternational5 November 2026
A Systematic Benchmark for Evaluating Multimodal Personalized Reasoning of Vision-Language Models
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arXiv:2611.06259v1 Announce Type: new Abstract: People often make decisions by holistically reasoning over heterogeneous forms of personal information. In this paper, we study the relatively underexplored capability of multimodal personalized reasoning in multimodal large language models (MLLMs). To this end, we introduce \texttt{MPRBench}, a novel and comprehensive benchmark specifically designed to evaluate personalized reasoning across a wide range of tasks and real-world challenges. \texttt{MPRBench} consists of 12 sub-tasks and additionally supports interpretable analysis of representativ
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