: Learning to predict ingredient quantities from recipe contexts

Donghee Choi, Mogan Gim, Samy Badreddine, Hajung Kim, Donghyeon Park, Jaewoo Kang

Abstract: Highlights•We introduce an ingredient quantity prediction task consisting of three sub-tasks.•We developed KitchenScale which performs the ingredient quantity prediction task.•KitchenScale adopts transfer learning of cooking knowledge from recipes to PLMs.•Robustness in KitchenScale is attributed to the DExp approach for the quantity regression task.