Paper ID: 2209.12774

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

Konstantinos Katserelis, Konstantinos Skianis

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.

Submitted: Sep 26, 2022