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Multimodal Neural Machine Translation: A Survey of the State of the Art

Yi Feng, Chuanyi Li, Jiatong He, Zhenyu Hou, Vincent Ng

2025Year
1Citations
1Top-tier citations

Abstract

Multimodal neural machine translation (MNMT) has received increasing attention due to its widespread applications in various fields such as cross-border e-commerce and cross-border social media platforms. The task aims to integrate other modalities, such as the visual modality, with textual data to enhance translation performance. We survey the major milestones in MNMT research, providing a comprehensive overview of relevant datasets and recent methodologies, and discussing key challenges and promising research directions.

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