{"url":"/task/nutrition","name":"Nutrition","slug":"nutrition","description_markdown":null,"categories":[{"name":"Miscellaneous","url":"/area/miscellaneous"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":202,"papers_with_code":33,"benchmarks":1,"benchmark_tables_in_archive":1,"benchmark_tables_shown":1,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":1,"subtasks":0,"parent_tasks":0},"benchmarks":[{"leaderboard":"/sota/nutrition-on-big-bench","slug":"nutrition-on-big-bench","dataset":"BIG-bench","dataset_url":"/dataset/big-bench","rows_in_archive":1,"metrics":["Accuracy "],"first_row_in_archive_order":{"model":"Gopher-280B (few-shot, k=5)","paper_title":"Scaling Language Models: Methods, Analysis & Insights from Training Gopher","paper_url":"/paper/scaling-language-models-methods-analysis-1","paper_date":"2021-12-08","arxiv_id":"2112.11446","code_links":[{"title":"allenai/dolma","url":"https://github.com/allenai/dolma"},{"title":"rvlopes/gloria","url":"https://github.com/rvlopes/gloria"},{"title":"bramiozo/PubScience","url":"https://github.com/bramiozo/PubScience"}],"syntology":null}}],"datasets":[{"url":"/dataset/big-bench","name":"BIG-bench","full_name":"Beyond the Imitation Game Benchmark","num_papers_in_archive":349}],"subtasks":[],"parent_tasks":[],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":30,"of":33,"tagged_in_all":202,"items":[{"url":"/paper/scaling-language-models-methods-analysis-1","title":"Scaling Language Models: Methods, Analysis & Insights from Training Gopher","date":"2021-12-08","arxiv_id":"2112.11446","repositories_listed":3,"syntology":null},{"url":"/paper/nutribullets-hybrid-multi-document-health","title":"Nutribullets Hybrid: Multi-document Health Summarization","date":"2021-04-08","arxiv_id":"2104.03465","repositories_listed":2,"syntology":null},{"url":"/paper/an-open-source-dataset-on-dietary-behaviors","title":"An Open-Source Dataset on Dietary Behaviors and DASH Eating Plan Optimization Constraints","date":"2020-10-15","arxiv_id":"2010.07531","repositories_listed":2,"syntology":null},{"url":"/paper/foodtracker-a-real-time-food-detection-mobile","title":"FoodTracker: A Real-time Food Detection Mobile Application by Deep Convolutional Neural Networks","date":"2019-09-13","arxiv_id":"1909.05994","repositories_listed":2,"syntology":null},{"url":"/paper/learning-cross-modal-embeddings-with","title":"Learning Cross-Modal Embeddings with Adversarial Networks for Cooking Recipes and Food Images","date":"2019-05-03","arxiv_id":"1905.01273","repositories_listed":2,"syntology":null},{"url":"/paper/voltex-food-volume-estimation-using-text","title":"VolTex: Food Volume Estimation using Text-Guided Segmentation and Neural Surface Reconstruction","date":"2025-06-03","arxiv_id":"2506.02895","repositories_listed":1,"syntology":null},{"url":"/paper/nutrigen-personalized-meal-plan-generator","title":"NutriGen: Personalized Meal Plan Generator Leveraging Large Language Models to Enhance Dietary and Nutritional Adherence","date":"2025-02-28","arxiv_id":"2502.20601","repositories_listed":1,"syntology":null},{"url":"/paper/cuckoo-an-ie-free-rider-hatched-by-massive","title":"Cuckoo: An IE Free Rider Hatched by Massive Nutrition in LLM's Nest","date":"2025-02-16","arxiv_id":"2502.11275","repositories_listed":1,"syntology":null},{"url":"/paper/dimb-re-mining-the-scientific-literature-for","title":"DiMB-RE: Mining the Scientific Literature for Diet-Microbiome Associations","date":"2024-09-29","arxiv_id":"2409.19581","repositories_listed":1,"syntology":null},{"url":"/paper/swine-diet-design-using-multi-objective","title":"Swine Diet Design using Multi-objective Regionalized Bayesian Optimization","date":"2024-09-19","arxiv_id":"2409.12919","repositories_listed":1,"syntology":null},{"url":"/paper/2408-02964","title":"Accuracy and Consistency of LLMs in the Registered Dietitian Exam: The Impact of Prompt Engineering and Knowledge Retrieval","date":"2024-08-06","arxiv_id":"2408.02964","repositories_listed":1,"syntology":null},{"url":"/paper/metafood-cvpr-2024-challenge-on-physically","title":"MetaFood CVPR 2024 Challenge on Physically Informed 3D Food Reconstruction: Methods and Results","date":"2024-07-12","arxiv_id":"2407.09285","repositories_listed":1,"syntology":null},{"url":"/paper/voleta-one-and-few-shot-food-volume","title":"VolETA: One- and Few-shot Food Volume Estimation","date":"2024-07-01","arxiv_id":"2407.01717","repositories_listed":1,"syntology":null},{"url":"/paper/res-vmamba-fine-grained-food-category-visual","title":"Res-VMamba: Fine-Grained Food Category Visual Classification Using Selective State Space Models with Deep Residual Learning","date":"2024-02-24","arxiv_id":"2402.15761","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_unverified":0,"n_pointer_only":3}},{"url":"/paper/diet-odin-a-novel-framework-for-opioid-misuse","title":"Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns","date":"2024-02-21","arxiv_id":"2403.08820","repositories_listed":1,"syntology":null},{"url":"/paper/synthesizing-knowledge-enhanced-features-for","title":"Synthesizing Knowledge-enhanced Features for Real-world Zero-shot Food Detection","date":"2024-02-14","arxiv_id":"2402.09242","repositories_listed":1,"syntology":null},{"url":"/paper/nhanes-gcp-leveraging-the-google-cloud","title":"NHANES-GCP: Leveraging the Google Cloud Platform and BigQuery ML for reproducible machine learning with data from the National Health and Nutrition Examination Survey","date":"2024-01-13","arxiv_id":"2401.06967","repositories_listed":1,"syntology":null},{"url":"/paper/k-perm-personalized-response-generation-using","title":"K-PERM: Personalized Response Generation Using Dynamic Knowledge Retrieval and Persona-Adaptive Queries","date":"2023-12-29","arxiv_id":"2312.17748","repositories_listed":1,"syntology":null},{"url":"/paper/towards-clinical-prediction-with-transparency","title":"Towards Clinical Prediction with Transparency: An Explainable AI Approach to Survival Modelling in Residential Aged Care","date":"2023-12-01","arxiv_id":"2312.00271","repositories_listed":1,"syntology":null},{"url":"/paper/vision-based-food-nutrition-estimation-via","title":"Vision-based Food Nutrition Estimation via RGB-D Fusion Network","date":"2023-10-25","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/ai4food-nutritionfw-a-novel-framework-for-the","title":"AI4Food-NutritionFW: A Novel Framework for the Automatic Synthesis and Analysis of Eating Behaviours","date":"2023-09-12","arxiv_id":"2309.06308","repositories_listed":1,"syntology":null},{"url":"/paper/cook-gen-robust-generative-modeling-of","title":"Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes","date":"2023-06-01","arxiv_id":"2306.01805","repositories_listed":1,"syntology":null},{"url":"/paper/on-the-hidden-mystery-of-ocr-in-large","title":"OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models","date":"2023-05-13","arxiv_id":"2305.07895","repositories_listed":1,"syntology":null},{"url":"/paper/synthetic-data-generation-for-a-longitudinal","title":"Synthetic data generation for a longitudinal cohort study -- Evaluation, method extension and reproduction of published data analysis results","date":"2023-05-12","arxiv_id":"2305.07685","repositories_listed":1,"syntology":null},{"url":"/paper/a-video-based-end-to-end-pipeline-for-non","title":"A Video-based End-to-end Pipeline for Non-nutritive Sucking Action Recognition and Segmentation in Young Infants","date":"2023-03-29","arxiv_id":"2303.16867","repositories_listed":1,"syntology":null},{"url":"/paper/ai4food-nutritiondb-food-image-database","title":"Leveraging Automatic Personalised Nutrition: Food Image Recognition Benchmark and Dataset based on Nutrition Taxonomy","date":"2022-11-14","arxiv_id":"2211.07440","repositories_listed":1,"syntology":null},{"url":"/paper/discomat-distantly-supervised-composition","title":"DiSCoMaT: Distantly Supervised Composition Extraction from Tables in Materials Science Articles","date":"2022-07-03","arxiv_id":"2207.01079","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":1}},{"url":"/paper/learning-personal-food-preferences-via-food","title":"Learning Personal Food Preferences via Food Logs Embedding","date":"2021-10-29","arxiv_id":"2110.15498","repositories_listed":1,"syntology":null},{"url":"/paper/nutri-bullets-summarizing-health-studies-by","title":"Nutri-bullets: Summarizing Health Studies by Composing Segments","date":"2021-03-22","arxiv_id":"2103.11921","repositories_listed":1,"syntology":null},{"url":"/paper/nutrition5k-towards-automatic-nutritional","title":"Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food","date":"2021-03-04","arxiv_id":"2103.03375","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":1}}],"syntology_records":3,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}