{"paper":{"title":"OmniFood-Bench: Evaluating VLMs for Nutrient Reasoning and Personalized Health Advice","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jingpu Yang, Miao Fang, Qian Jiang, Zhecheng Shi, Zirui Song","submitted_at":"2026-07-09T12:46:00Z","abstract_excerpt":"The rapid integration of Large Vision-Language Models (VLMs) into critical infrastructure promises to revolutionize\n  personalized healthcare and dietary management. However, in the domain of food systems, autonomous agents face a\n  unique and persistent challenge: the \"Systemic Information Asymmetry\" between visual appearance and intrinsic\n  nutritional composition. Existing benchmarks primarily focus on coarse-grained classification tasks, such as food\n  category recognition, which fail to evaluate the intricate reasoning chain required for real-world dietary management\n  -- specifically, th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.08423","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.08423/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}