Recipe Completion

Recipe completion research focuses on automatically generating, revising, and personalizing cooking recipes using computational methods. Current efforts leverage large language models (LLMs), often multimodal and incorporating visual information from images or videos, along with graph-based and transformer-based architectures to improve ingredient suggestion, instruction ordering, and overall recipe coherence. This work has significant implications for personalized dietary planning, assistive cooking technologies, and advancing the intersection of natural language processing and computer vision in the culinary domain.