# RecipeGPT: Generative Pre-training Based Cooking Recipe Generation and Evaluation System

arXiv: https://arxiv.org/abs/2003.02498 · HTML: https://mlsanity.com/paper/2003.02498/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Mar 2020.

## Built on by (most cited first, 30 of 34)

- [On the Creativity of Large Language Models](https://mlsanity.com/paper/2304.00008/) (2023)
- [A Large-Scale Benchmark for Food Image Segmentation](https://mlsanity.com/paper/2105.05409/) (2021)
- [FoodLMM: A Versatile Food Assistant using Large Multi-modal Model](https://mlsanity.com/paper/2312.14991/) (2023)
- [Creativity and Machine Learning: A Survey](https://mlsanity.com/paper/2104.02726/) (2021)
- [Why is constrained neural language generation particularly challenging?](https://mlsanity.com/paper/2206.05395/) (2022)
- [Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challenges](https://mlsanity.com/paper/2405.15604/) (2024)
- [SHARE: a System for Hierarchical Assistive Recipe Editing](https://mlsanity.com/paper/2105.08185/) (2021)
- [LLaVA-Chef: A Multi-modal Generative Model for Food Recipes](https://mlsanity.com/paper/2408.16889/) (2024)
- [ChefFusion: Multimodal Foundation Model Integrating Recipe and Food Image Generation](https://mlsanity.com/paper/2409.12010/) (2024)
- [Transferring Knowledge from Text to Video: Zero-Shot Anticipation for Procedural Actions](https://mlsanity.com/paper/2106.03158/) (2021)
- [Cultural Adaptation of Recipes](https://mlsanity.com/paper/2310.17353/) (2023)
- [Counterfactual Recipe Generation: Exploring Compositional Generalization in a Realistic Scenario](https://mlsanity.com/paper/2210.11431/) (2022)
- [Plug-and-Play Recipe Generation with Content Planning](https://mlsanity.com/paper/2212.05093/) (2022)
- [Control Large Language Models via Divide and Conquer](https://mlsanity.com/paper/2410.04628/) (2024)
- [Ratatouille: A tool for Novel Recipe Generation](https://mlsanity.com/paper/2206.08267/) (2022)
- [RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer](https://mlsanity.com/paper/2210.10628/) (2022)
- [ENCONTER: Entity Constrained Progressive Sequence Generation via Insertion-based Transformer](https://mlsanity.com/paper/2103.09548/) (2021)
- [Monte Carlo Tree Search for Recipe Generation using GPT-2](https://mlsanity.com/paper/2401.05199/) (2024)
- [Retrieval Augmented Recipe Generation](https://mlsanity.com/paper/2411.08715/) (2024)
- [Can We Enhance Bug Report Quality Using LLMs?: An Empirical Study of LLM-Based Bug Report Generation](https://mlsanity.com/paper/2504.18804/) (2025)
- [Cooking Up Creativity: Enhancing LLM Creativity through Structured Recombination](https://mlsanity.com/paper/2504.20643/) (2025)
- [Assistive Recipe Editing through Critiquing](https://mlsanity.com/paper/2205.02454/) (2022)
- [Assorted, Archetypal and Annotated Two Million (3A2M) Cooking Recipes Dataset based on Active Learning](https://mlsanity.com/paper/2303.16778/) (2023)
- [KitchenScale: Learning to predict ingredient quantities from recipe contexts](https://mlsanity.com/paper/2304.10739/) (2023)
- [GIRT-Model: Automated Generation of Issue Report Templates](https://mlsanity.com/paper/2402.02632/) (2024)
- [KERL: Knowledge-Enhanced Personalized Recipe Recommendation using Large Language Models](https://mlsanity.com/paper/2505.14629/) (2025)
- [Towards Consistent Language Models Using Declarative Constraints](https://mlsanity.com/paper/2312.15472/) (2023)
- [RecipeGen: A Benchmark for Real-World Recipe Image Generation](https://mlsanity.com/paper/2503.05228/) (2025)
- [Culinary Class Wars: Evaluating LLMs using ASH in Cuisine Transfer Task](https://mlsanity.com/paper/2411.01996/) (2024)
- [RecipeGen: A Step-Aligned Multimodal Benchmark for Real-World Recipe Generation](https://mlsanity.com/paper/2506.06733/) (2025)

## Abstract (arXiv)

Interests in the automatic generation of cooking recipes have been growing steadily over the past few years thanks to a large amount of online cooking recipes. We present RecipeGPT, a novel online recipe generation and evaluation system. The system provides two modes of text generations: (1) instruction generation from given recipe title and ingredients; and (2) ingredient generation from recipe title and cooking instructions. Its back-end text generation module comprises a generative pre-trained language model GPT-2 fine-tuned on a large cooking recipe dataset. Moreover, the recipe evaluation module allows the users to conveniently inspect the quality of the generated recipe contents and store the results for future reference. RecipeGPT can be accessed online at https://recipegpt.org/.