Recipe Generation
10 papers with code • 5 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Recipe Generation
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Recipe1M+
RecipeNLG
Food.com Recipes and Interactions
Most implemented papers
Inverse Cooking: Recipe Generation from Food Images
facebookresearch/inversecooking
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CVPR 2019
Our system predicts ingredients as sets by means of a novel architecture, modeling their dependencies without imposing any order, and then generates cooking instructions by attending to both image and its inferred ingredients simultaneously.
Building Language Models for Text with Named Entities
uclanlp/NamedEntityLanguageModel
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ACL 2018
Text in many domains involves a significant amount of named entities.
Generating Personalized Recipes from Historical User Preferences
majumderb/recipe-personalization
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IJCNLP 2019
Existing approaches to recipe generation are unable to create recipes for users with culinary preferences but incomplete knowledge of ingredients in specific dishes.
RecipeGPT: Generative Pre-training Based Cooking Recipe Generation and Evaluation System
LARC-CMU-SMU/RecipeGPT-exp
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Interests in the automatic generation of cooking recipes have been growing steadily over the past few years thanks to a large amount of online cooking recipes.
Structure-Aware Generation Network for Recipe Generation from Images
We investigate an open research task of generating cooking instructions based on only food images and ingredients, which is similar to the image captioning task.
RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation
Glorf/recipenlg
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We use the dataset to approach the problem of generating recipes.
SHARE: a System for Hierarchical Assistive Recipe Editing
The large population of home cooks with dietary restrictions is under-served by existing cooking resources and recipe generation models.
Counterfactual Recipe Generation: Exploring Compositional Generalization in a Realistic Scenario
Although pretrained language models can generate fluent recipe texts, they fail to truly learn and use the culinary knowledge in a compositional way.
Learning to Substitute Ingredients in Recipes
Recipe personalization through ingredient substitution has the potential to help people meet their dietary needs and preferences, avoid potential allergens, and ease culinary exploration in everyone's kitchen.
LongForm: Optimizing Instruction Tuning for Long Text Generation with Corpus Extraction
Our models outperform 10x larger language models without instruction tuning on various tasks such as story/recipe generation and long-form question answering.
