We investigate the use of Large Language Models (LLMs) to adapt and align generated recipes and dialogues with individual preferences, values, and sustainability goals, utilizing AI to personalize dietary recommendations. By integrating user data—including health profiles, ethical values, and environmental concerns—into sophisticated AI algorithms, the research aims to refine how LLMs dynamically generate and adjust content to promote adherence to plant-based diets.
The study focuses on the efficacy of AI-driven recipe and argument adaptations, contributing insights into the fields of food science and consumer science on harnessing AI to facilitate sustainable eating behaviors.
Jonathan Sigh Musso - Bachelor of Machine Learning & Data Science - University of Copenhagen
Lukas Mikelionis - Data Engineer, MSc graduate in Computer Science - University of Copenhagen
Daniel Hershcovich - Tenure-Track Assistant Professor, PhD Department of Computer Science - University of Copenhagen
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