A new benchmark shows current vision-language models can name foods but fail at estimating portion and nutrient values and often give unsafe dietary advice for chronic-disease patients.
MM-Food-100K: A 100,000-Sample Multimodal Food Intelligence Dataset with Verifiable Provenance
2 Pith papers cite this work. Polarity classification is still indexing.
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abstract
We present MM-Food-100K, a public 100,000-sample multimodal food intelligence dataset with verifiable provenance. It is a curated approximately 10% open subset of an original 1.2 million, quality-accepted corpus of food images annotated for a wide range of information (such as dish name, region of creation). The corpus was collected over six weeks from over 87,000 contributors using the Codatta contribution model, which combines community sourcing with configurable AI-assisted quality checks; each submission is linked to a wallet address in a secure off-chain ledger for traceability, with a full on-chain protocol on the roadmap. We describe the schema, pipeline, and QA, and validate utility by fine-tuning large vision-language models (ChatGPT 5, ChatGPT OSS, Qwen-Max) on image-based nutrition prediction. Fine-tuning yields consistent gains over out-of-box baselines across standard metrics; we report results primarily on the MM-Food-100K subset. We release MM-Food-100K for publicly free access and retain approximately 90% for potential commercial access with revenue sharing to contributors.
years
2026 2representative citing papers
Introduces CalorieBench-80K benchmark with CoT calorie reasoning and Food-R1 VLM trained via CoT cold-start then GRPO reinforcement fine-tuning, claiming consistent outperformance on food tasks.
citing papers explorer
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OmniFood-Bench: Evaluating VLMs for Nutrient Reasoning and Personalized Health Advice
A new benchmark shows current vision-language models can name foods but fail at estimating portion and nutrient values and often give unsafe dietary advice for chronic-disease patients.
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Food-R1: A Unified Multi-Task Food Vision-Language Model with Reinforcement Learning
Introduces CalorieBench-80K benchmark with CoT calorie reasoning and Food-R1 VLM trained via CoT cold-start then GRPO reinforcement fine-tuning, claiming consistent outperformance on food tasks.