FAM-Bench: A Multimodal Benchmark for Condition-Aware Food-as-Medicine Reasoning 文章

ArXiv CS.AI2026-06-01NEWSen作者: Mingyang Mao, Bhargav Rishi Medisetti, Utkarsh Grover, Tanvir Ibrahim, Wenyan Li, Tingting Zhang, Xiaomin Lin

摘要

arXiv:2605.31410v1 Announce Type: new Abstract: Food-as-Medicine requires models to reason beyond what a dish is or what nutrition it contains: they must decide whether a concrete food choice is appropriate for a specific health condition. Existing food AI benchmarks primarily evaluate dish recognition, recipe understanding, nutrient estimation, or general nutrition question answering, leaving this health-aware decision layer largely untested. We introduce FAM-Bench, a multi-modal Food-as-Medicine benchmark with 2500 nutrition-expert-verified instances across 13 diet-related health conditions. The benchmark contains two complementary tasks: dish-level suitability assessment, where models judge whether a dish is suitable for a condition from its image and ingredient list, and comparative dish analysis, where models rank four candidate dishes by condition-specific suitability.

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