lishuyang/recipepairs

Tasks

• text-generation

Citation text from the card

@inproceedings{li-etal-2022-share,
    title = "{SHARE}: a System for Hierarchical Assistive Recipe Editing",
    author = "Li, Shuyang  and
      Li, Yufei  and
      Ni, Jianmo  and
      McAuley, Julian",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.emnlp-main.761",
    pages = "11077--11090",
    abstract = "The large population of home cooks with dietary restrictions is under-served by existing cooking resources and recipe generation models. To help them, we propose the task of controllable recipe editing: adapt a base recipe to satisfy a user-specified dietary constraint. This task is challenging, and cannot be adequately solved with human-written ingredient substitution rules or existing end-to-end recipe generation models. We tackle this problem with SHARE: a System for Hierarchical Assistive Recipe Editing, which performs simultaneous ingredient substitution before generating natural-language steps using the edited ingredients. By decoupling ingredient and step editing, our step generator can explicitly integrate the available ingredients. Experiments on the novel RecipePairs dataset{---}83K pairs of similar recipes where each recipe satisfies one of seven dietary constraints{---}demonstrate that SHARE produces convincing, 

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