KitchenScale: Learning to predict ingredient quantities from recipe contexts. (arXiv:2304.10739v1 [cs.CL])

Determining proper quantities for ingredients is an essential part of cooking
practice from the perspective of enriching tastiness and promoting healthiness.
We introduce KitchenScale, a fine-tuned Pre-trained Language Model (PLM) that
predicts a target ingredient's quantity and measurement unit given its recipe
context. To effectively train our KitchenScale model, we formulate an
ingredient quantity prediction task that consists of three sub-tasks which are
ingredient measurement type classification, unit classification, and quantity
regression task. Furthermore, we utilized transfer learning of cooking …

arxiv classification context cooking knowledge language language model measurement part perspective practice prediction recipe regression transfer transfer learning type