Towards Fine-Dining Recipe Generation with Generative Pre-trained Transformers
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 13 of its 34 references that are in the map. First posted on arXiv 26 Sep 2022.
Builds on
13 of 34 references.
References · 13
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- 2018Inverse Cooking: Recipe Generation from Food Imagescited by 47
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Citing papers per year: 2023: 1.
1 paper.