Recipe Generation
5개 벤치마크 · 논문 47편 · 이 태스크의 논문 보기 →
Benchmarks
Most implemented
Inverse Cooking: Recipe Generation from Food Images
LongForm: Effective Instruction Tuning with Reverse Instructions
Building Language Models for Text with Named Entities
KERL: Knowledge-Enhanced Personalized Recipe Recommendation using Large Language Models
Instruction Following without Instruction Tuning
Papers
Fusing Semantic, Lexical, and Domain Perspectives for Recipe Similarity Estimation
This research focuses on developing advanced methods for assessing similarity between recipes by combining different sources of information and analytical approaches. We explore the semantic, lexical, and domain similari…
Recipe GenerationCan LLMs Cook Jamaican Couscous? A Study of Cultural Novelty in Recipe Generation
Large Language Models (LLMs) are increasingly used to generate and shape cultural content, ranging from narrative writing to artistic production. While these models demonstrate impressive fluency and generative capacity,…
Recipe GenerationDataChef: Cooking Up Optimal Data Recipes for LLM Adaptation via Reinforcement Learning
In the current landscape of Large Language Models (LLMs), the curation of large-scale, high-quality training data is a primary driver of model performance. A key lever is the \emph{data recipe}, which comprises a data pr…
Reinforcement LearningRecipe GenerationEnhancing Action and Ingredient Modeling for Semantically Grounded Recipe Generation
Recent advances in Multimodal Large Language Models (MLMMs) have enabled recipe generation from food images, yet outputs often contain semantically incorrect actions or ingredients despite high lexical scores (e.g., BLEU…
Recipe GenerationLosses that Cook: Topological Optimal Transport for Structured Recipe Generation
Cooking recipes are complex procedures that require not only a fluent and factual text, but also accurate timing, temperature, and procedural coherence, as well as the correct composition of ingredients. Standard trainin…
Recipe GenerationPoint CloudsEfficient Test-Time Retrieval Augmented Generation
Although Large Language Models (LLMs) demonstrate significant capabilities, their reliance on parametric knowledge often leads to inaccuracies. Retrieval Augmented Generation (RAG) mitigates this by incorporating externa…
Open-Domain Question AnsweringRecipe GenerationImage Captioning