2023/10/26 by Yong Cao, Cao, Yong, Yova Kementchedjhieva +14 · 1 voice · 2 citations
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Computer Science · Social Sciences · #Artificial Intelligence (cs.AI) #Cancer-related molecular mechanisms research #Computation and Language (cs.CL) #Computational and Text Analysis Methods #Culinary Culture and Tourism #FOS: Computer and information sciences #cs.AI #cs.CL
paper · pdf · doi:10.48550/arxiv.2310.17353
openalex publication_date 2023/10/26 · arxiv published 2023/10/26 · arxiv updated 2023/10/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Building upon the considerable advances in Large Language Models (LLMs), we are now equipped to address more sophisticated tasks demanding a nuanced understanding of cross-cultural contexts. A key example is recipe adaptation, which goes beyond simple translation to include a grasp of ingredients, culinary techniques, and dietary preferences specific to a given culture. We introduce a new task involving the translation and cultural adaptation of recipes between Chinese and English-speaking cuisines. To support this investigation, we present CulturalRecipes, a unique dataset comprised of automatically paired recipes written in Mandarin Chinese and English. This dataset is further enriched with a human-written and curated test set. In this intricate task of cross-cultural recipe adaptation, we evaluate the performance of various methods, including GPT-4 and other LLMs, traditional machine translation, and information retrieval techniques. Our comprehensive analysis includes both automatic and human evaluation metrics. While GPT-4 exhibits impressive abilities in adapting Chinese recipes into English, it still lags behind human expertise when translating English recipes into Chinese. This underscores the multifaceted nature of cultural adaptations. We anticipate that these insights will significantly contribute to future research on culturally-aware language models and their practical application in culturally diverse contexts.