@inproceedings{wu-etal-2024-transagents,
    title = "{T}rans{A}gents: Build Your Translation Company with Language Agents",
    author = "Wu, Minghao  and
      Xu, Jiahao  and
      Wang, Longyue",
    editor = "Hernandez Farias, Delia Irazu  and
      Hope, Tom  and
      Li, Manling",
    booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    month = nov,
    year = "2024",
    address = "Miami, Florida, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/moar-dois/2024.emnlp-demo.14/",
    doi = "10.18653/v1/2024.emnlp-demo.14",
    pages = "131--141",
    abstract = "Multi-agent systems empowered by large language models (LLMs) have demonstrated remarkable capabilities in a wide range of downstream applications. In this work, we introduce TransAgents, a novel multi-agent translation system inspired by human translation companies. TransAgents employs specialized agents{---}Senior Editor, Junior Editor, Translator, Localization Specialist, and Proofreader{---}to collaboratively produce translations that are accurate, culturally sensitive, and of high quality. Our system is flexible, allowing users to configure their translation company based on specific needs, and universal, with empirical evidence showing superior performance across various domains compared to state-of-the-art methods. Additionally, TransAgents features a user-friendly interface and offers translations at a cost approximately $80\times$ cheaper than professional human translation services. Evaluations on literary, legal, and financial test sets demonstrate that TransAgents produces translations preferred by human evaluators, even surpassing human-written references in literary contexts. Our live demo website is available at https://www.transagents.ai/. Our demonstration video is available at https://www.youtube.com/watch?v=p7jIAtF-WKc."
}