Papers Recipe Generation
“Recipe Generation” 태그가 달린 논문 47편 · 필터 해제
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 CaptioningThe Digital Sous Chef -- A Comparative Study on Fine-Tuning Language Models for Recipe Generation
We established a rigorous benchmark for text-based recipe generation, a fundamental task in natural language generation. We present a comprehensive comparative study contrasting a fine-tuned GPT-2 large (774M) model agai…
Recipe GenerationRecipeGen: A Step-Aligned Multimodal Benchmark for Real-World Recipe Generation
Creating recipe images is a key challenge in food computing, with applications in culinary education and multimodal recipe assistants. However, existing datasets lack fine-grained alignment between recipe goals, step-wis…
Recipe GenerationFew-Shot Test-Time Optimization Without Retraining for Semiconductor Recipe Generation and Beyond
We introduce Model Feedback Learning (MFL), a novel test-time optimization framework for optimizing inputs to pre-trained AI models or deployed hardware systems without requiring any retraining of the models or modificat…
Bayesian OptimizationRecipe GenerationKERL: Knowledge-Enhanced Personalized Recipe Recommendation using Large Language Models
Recent advances in large language models (LLMs) and the abundance of food data have resulted in studies to improve food understanding using LLMs. Despite several recommendation systems utilizing LLMs and Knowledge Graphs…
Food recommendationKnowledge GraphsRecipe GenerationRecommendation SystemsFine-tuning Language Models for Recipe Generation: A Comparative Analysis and Benchmark Study
This research presents an exploration and study of the recipe generation task by fine-tuning various very small language models, with a focus on developing robust evaluation metrics and comparing across different languag…
Recipe GenerationRetrieval Augmented Recipe Generation
Given the potential applications of generating recipes from food images, this area has garnered significant attention from researchers in recent years. Existing works for recipe generation primarily utilize a two-stage t…
Recipe GenerationRetrievalCulinary Class Wars: Evaluating LLMs using ASH in Cuisine Transfer Task
The advent of Large Language Models (LLMs) have shown promise in various creative domains, including culinary arts. However, many LLMs still struggle to deliver the desired level of culinary creativity, especially when t…
Recipe GenerationFoodMLLM-JP: Leveraging Multimodal Large Language Models for Japanese Recipe Generation
Research on food image understanding using recipe data has been a long-standing focus due to the diversity and complexity of the data. Moreover, food is inextricably linked to people's lives, making it a vital research a…
Recipe GenerationInstruction Following without Instruction Tuning
Instruction tuning commonly means finetuning a language model on instruction-response pairs. We discover two forms of adaptation (tuning) that are deficient compared to instruction tuning, yet still yield instruction fol…
Instruction FollowingLanguage ModelingLanguage ModellingRecipe GenerationChefFusion: Multimodal Foundation Model Integrating Recipe and Food Image Generation
Significant work has been conducted in the domain of food computing, yet these studies typically focus on single tasks such as t2t (instruction generation from food titles and ingredients), i2t (recipe generation from fo…
DecoderFood RecognitionImage GenerationRecipe GenerationLLaVA-Chef: A Multi-modal Generative Model for Food Recipes
In the rapidly evolving landscape of online recipe sharing within a globalized context, there has been a notable surge in research towards comprehending and generating food recipes. Recent advancements in large language …
Recipe GenerationTowards Automated Solution Recipe Generation for Industrial Asset Management with LLM
This study introduces a novel approach to Industrial Asset Management (IAM) by incorporating Conditional-Based Management (CBM) principles with the latest advancements in Large Language Models (LLMs). Our research introd…
Asset ManagementManagementRecipe GenerationDeep Learning Based Named Entity Recognition Models for Recipes
Food touches our lives through various endeavors, including flavor, nourishment, health, and sustainability. Recipes are cultural capsules transmitted across generations via unstructured text. Automated protocols for rec…
Deep Learningnamed-entity-recognitionNamed Entity RecognitionNER+1Monte Carlo Tree Search for Recipe Generation using GPT-2
Automatic food recipe generation methods provide a creative tool for chefs to explore and to create new, and interesting culinary delights. Given the recent success of large language models (LLMs), they have the potentia…
Recipe GenerationText Generation