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 1–25 of 108 papers

TitleStatusHype
Seamless: Multilingual Expressive and Streaming Speech TranslationCode6
Attention Is All You NeedCode3
3AM: An Ambiguity-Aware Multi-Modal Machine Translation DatasetCode1
CLIPTrans: Transferring Visual Knowledge with Pre-trained Models for Multimodal Machine TranslationCode1
BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine TranslationCode1
Scene Graph as Pivoting: Inference-time Image-free Unsupervised Multimodal Machine Translation with Visual Scene HallucinationCode1
Tackling Ambiguity with Images: Improved Multimodal Machine Translation and Contrastive EvaluationCode1
Distill the Image to Nowhere: Inversion Knowledge Distillation for Multimodal Machine TranslationCode1
VALHALLA: Visual Hallucination for Machine TranslationCode1
Neural Machine Translation with Phrase-Level Universal Visual RepresentationsCode1
On Vision Features in Multimodal Machine TranslationCode1
MSCTD: A Multimodal Sentiment Chat Translation DatasetCode1
VISA: An Ambiguous Subtitles Dataset for Visual Scene-Aware Machine TranslationCode1
BERTGEN: Multi-task Generation through BERTCode1
Cross-lingual Visual Pre-training for Multimodal Machine TranslationCode1
Dynamic Context-guided Capsule Network for Multimodal Machine TranslationCode1
Multimodal Transformer for Multimodal Machine TranslationCode1
Self-Knowledge Distillation with Progressive Refinement of TargetsCode1
M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-trainingCode1
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
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All datasetsMulti30KHindi Visual Genome (Challenge Set)Hindi Visual Genome (Test Set)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1delMeteor (EN-FR)74.6—Unverified
2ERNIE-UniX2BLEU (EN-DE)49.3—Unverified
3IKD-MMTBLEU (EN-DE)41.28—Unverified
4DCCNBLEU (EN-DE)39.7—Unverified
5CaglayanBLEU (EN-DE)39.4—Unverified
6Gumbel-Attention MMTBLEU (EN-DE)39.2—Unverified
7Multimodal TransformerBLEU (EN-DE)38.7—Unverified
8ImagiTBLEU (EN-DE)38.4—Unverified
9del+objBLEU (EN-DE)38—Unverified
10VMMTFBLEU (EN-DE)37.6—Unverified
#ModelMetricClaimedVerifiedStatus
1ViTABLEU (EN-HI)51.6—Unverified
#ModelMetricClaimedVerifiedStatus
1ViTABLEU (EN-HI)44.6—Unverified