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Cross Lingual Document Classification On
Metrics
Accuracy
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| 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 | |
| MultiCCA + CNN | 81.2% | A Corpus for Multilingual Document Classification in Eight Languages | |
| BiLSTM (Europarl) | 71.83% | A Corpus for Multilingual Document Classification in Eight Languages |
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