  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, coherent recipes that are appropriate for a target dietary
constraint. We further show through human evaluations and real-world cooking
trials that recipes edited by SHARE can be easily followed by home cooks to
create appealing dishes.
