Research map / Architectures and efficiency / RNNs and normalization
MLSLT: Towards Multilingual Sign Language Translation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use dynamic routing with InterLSR and IntraLSR instead of the multilingual baseline | MSLT on SP-10, sign languages to English · SP-10 test | BLEU4: 2.12 -> 4.66 | Helped |
| Use dynamic routing with InterLSR and IntraLSR instead of separate bilingual models | MSLT on SP-10, sign languages to English · SP-10 test | ROUGE: 30.86 -> 32.70 | Helped |
| Use MLSLT rather than separate bilingual models | BFI to spoken languages on SP-10 · SP-10 test | BLEU4: 1.75 -> 2.55 | Helped |
| Use MLSLT rather than separate bilingual models | BFI to spoken languages on SP-10 · SP-10 test | ROUGE: 29.69 -> 31.47 | Helped |
| Use MLSLT rather than separate bilingual models for 10×10 language pairs | Many-to-many translation on SP-10 · SP-10, 10×10 language pairs | BLEU4: 1.66 -> 1.88 | Helped |
| Use MLSLT rather than separate bilingual models for 10×10 language pairs | Many-to-many translation on SP-10 · SP-10, 10×10 language pairs | ROUGE: 29.27 -> 30.26 | Helped |
| Translate without supervised examples for the evaluated sign-language-to-English pair | Zero-shot MLSLT · SP-10 zero-shot sign languages to English | BLEU4: 3.47 -> 2.69; 3.60 -> 3.44; 3.83 -> 3.29; 3.83 -> 3.14; 2.94 -> 2.65; 2.99 -> 2.40; 2.46 -> 1.03; 4.32 -> 1.78; 3.23 -> | Mixed |
| Add IntraLSR (ablation) | Native SLT on SP-10 · SP-10 | BLEU4: 2.27 -> 5.19 | Helped |
| Add IntraLSR (ablation) | Native SLT on SP-10 · SP-10 | ROUGE: 29.80 -> 33.33 | Helped |
| Add InterLSR (ablation) | Native SLT on SP-10 · SP-10 | BLEU4: 2.27 -> 3.58 | Helped |
| Add InterLSR (ablation) | Native SLT on SP-10 · SP-10 | ROUGE: 29.80 -> 32.20 | Helped |
| Add both IntraLSR and InterLSR (ablation) | Native SLT on SP-10 · SP-10 | BLEU4: 2.27 -> 6.30 | Helped |
Closest papers by meaning
- Scaling Sign Language Translation (NeurIPS 2024 · similarity 0.91)
- LLMs are Good Sign Language Translators (CVPR 2024 · similarity 0.89)
- YouTube-SL-25: A Large-Scale, Open-Domain Multilingual Sign Language Parallel Corpus (ICLR 2025 · similarity 0.88)
- Sign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation (ICLR 2024 · similarity 0.88)
- Lost in Translation, Found in Context: Sign Language Translation with Contextual Cues (CVPR 2025 · similarity 0.88)
- KD-MSLRT: Lightweight Sign Language Recognition Model Based on Mediapipe and 3D to 1D Knowledge Distillation (AAAI 2025 · similarity 0.88)
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