@inproceedings{lu-etal-2025-vidove,
    title = "{V}i{D}ove: A Translation Agent System with Multimodal Context and Memory-Augmented Reasoning",
    author = "Lu, Yichen  and
      Dai, Wei  and
      Liu, Jiaen  and
      Kwok, Ching Wing  and
      Wu, Zongheng  and
      Xiao, Xudong  and
      Sun, Ao  and
      Fu, Sheng  and
      Zhan, Jianyuan  and
      Wang, Yian  and
      Saito, Takatomo  and
      Lai, Sicheng",
    editor = {Habernal, Ivan  and
      Schulam, Peter  and
      Tiedemann, J{\"o}rg},
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/name-variant-enfa-fane/2025.emnlp-demos.17/",
    doi = "10.18653/v1/2025.emnlp-demos.17",
    pages = "228--243",
    ISBN = "979-8-89176-334-0",
    abstract = "LLM-based translation agents have achieved highly human-like translation results and are capable of handling longer and more complex contexts with greater efficiency. However, they are typically limited to text-only inputs. In this paper, we introduce ViDove, a translation agent system designed for multimodal input. Inspired by the workflow of human translators, ViDove leverages visual and contextual background information to enhance the translation process. Additionally, we integrate a multimodal memory system and long-short term memory modules enriched with domain-specific knowledge, enabling the agent to perform more accurately and adaptively in real-world scenarios. As a result, ViDove achieves significantly higher translation quality in both subtitle generation and general translation tasks, with a 28{\%} improvement in BLEU scores and a 15{\%} improvement in SubER compared to previous state-of-the-art baselines. Moreover, we introduce DoveBench, a new benchmark for long-form automatic video subtitling and translation, featuring 17 hours of high-quality, human-annotated data. Our demo is available here: https://vidove.willbe03.com/"
}