Search Results for author:
Found 4 papers, 3 papers with code
CookingSense: A Culinary Knowledgebase with Multidisciplinary Assertions
This paper introduces CookingSense, a descriptive collection of knowledge assertions in the culinary domain extracted from various sources, including web data, scientific papers, and recipes, from which knowledge covering a broad range of aspects is acquired.
MolPLA: A Molecular Pretraining Framework for Learning Cores, R-Groups and their Linker Joints
Molecular core structures and R-groups are essential concepts in drug development.
KitchenScale: Learning to predict ingredient quantities from recipe contexts
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.
RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer
To perform this task, we developed RecipeMind, a food affinity score prediction model that quantifies the suitability of adding an ingredient to set of other ingredients.
