Optimizing Ingredient Substitution Using Large Language Models to Enhance Phytochemical Content in Recipes

In the emerging field of computational gastronomy, aligning culinary practices with scientifically supported nutritional goals is increasingly important. This study explores how large language models (LLMs) can be applied to optimize ingredient substitutions in recipes, specifically to enhance the p...

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Bibliographic Details
Main Authors: Luís Rita, Joshua Southern, Ivan Laponogov, Kyle Higgins, Kirill Veselkov
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Machine Learning and Knowledge Extraction
Subjects:
Online Access:https://www.mdpi.com/2504-4990/6/4/131
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