Towards Fine-Dining Recipe Generation with Generative Pre-trained Transformers

Food is essential to human survival. So much so that we have developed different recipes to suit our taste needs. In this work, we propose a novel way of creating new, fine-dining recipes from scratch using Transformers, specifically auto-regressive language models. Given a small dataset of food rec...

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Bibliographic Details
Published in:arXiv.org 2022-09
Main Authors: Katserelis, Konstantinos, Skianis, Konstantinos
Format: Article
Language:English
Subjects:
Autoregressive models
Cooking
Online Access:Get full text
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Summary:Food is essential to human survival. So much so that we have developed different recipes to suit our taste needs. In this work, we propose a novel way of creating new, fine-dining recipes from scratch using Transformers, specifically auto-regressive language models. Given a small dataset of food recipes, we try to train models to identify cooking techniques, propose novel recipes, and test the power of fine-tuning with minimal data.
ISSN:2331-8422