2025
IJCNLP
IJCNLP 2025
Findings of WAT2025 English-to-Indic Multimodal Translation Task
Abstract
AbstractThis paper presents the findings of the English-to-Indic Multimodal Translation shared task from the Workshop on Asian Translation (WAT2025). The task featured three tracks: text-only translation, image captioning, and multimodal translation across four low-resource Indic languages: Hindi, Bengali, Malayalam, and Odia. Three teams participated, submitting systems that achieved competitive performance, with BLEU scores ranging from 40.1 to 64.3 across different language pairs and tracks.
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio