Cross Lingual Document Classification On
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy | Paper Title | Repository |
|---|---|---|---|
| BiLSTM (Europarl) | 71.83% | A Corpus for Multilingual Document Classification in Eight Languages | - |
| MultiCCA + CNN | 81.2% | A Corpus for Multilingual Document Classification in Eight Languages | - |
| XLMft UDA | 96.95% | Bridging the domain gap in cross-lingual document classification | - |
| MultiFiT, pseudo | 91.62% | MultiFiT: Efficient Multi-lingual Language Model Fine-tuning | - |
| Massively Multilingual Sentence Embeddings | 84.78% | Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond | - |
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