Papers by Dhruva Patil

1 papers
Detect, Disambiguate, and Translate: On-Demand Visual Reasoning for Multimodal Machine Translation with Large Vision-Language Models (2025.naacl-long)

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Challenge: Multimodal machine translation (MMT) aims to leverage additional modalities beyond text . current MMT systems rely heavily on monolingual English captioning data .
Approach: They propose a reasoning-based framework to leverage large-scale vision-language models for MMT . they propose Detect, Disambiguate, and Translate framework to detect ambiguity in input sentence .
Outcome: The proposed framework outperforms state-of-the-art models in disambiguation accuracy and translation quality.

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