SOTAVerified

Multimodal Machine Translation

Multimodal machine translation is the task of doing machine translation with multiple data sources - for example, translating "a bird is flying over water" + an image of a bird over water to German text.

( Image credit: Findings of the Third Shared Task on Multimodal Machine Translation )

Papers

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Showing 1–10 of 108 papers

TitleStatusHype
CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation—0
Multimodal Machine Translation with Visual Scene Graph Pruning—0
TopicVD: A Topic-Based Dataset of Video-Guided Multimodal Machine Translation for DocumentariesCode0
Florenz: Scaling Laws for Systematic Generalization in Vision-Language Models—0
Make Imagination Clearer! Stable Diffusion-based Visual Imagination for Multimodal Machine Translation—0
EMMeTT: Efficient Multimodal Machine Translation Training—0
Towards Zero-Shot Multimodal Machine TranslationCode0
3AM: An Ambiguity-Aware Multi-Modal Machine Translation DatasetCode1
Exploring the Necessity of Visual Modality in Multimodal Machine Translation using Authentic Datasets—0
Adding Multimodal Capabilities to a Text-only Translation Model—0
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All datasetsMulti30KHindi Visual Genome (Challenge Set)Hindi Visual Genome (Test Set)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTABLEU (EN-HI)44.6—Unverified