Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph (2021.findings-emnlp)
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| Challenge: | Existing approaches to cross-lingual text classification require task-specific training data in high-resource sources . labeling cost, task characteristics, and privacy concerns can hinder the use of cross-linguistic training . |
| Approach: | They propose a dictionary-based heterogeneous graph (DHGNet) that uses bilingual dictionaries for task-independent word embeddings. |
| Outcome: | The proposed method outperforms pretrained models even though it does not access to large corpora. |
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