Papers with unsupervised transfer
Improving Low-Resource Cross-lingual Parsing with Expected Statistic Regularization (2023.tacl-1)
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| Challenge: | Existing methods for cross-lingual syntactic analysis have been shown to be effective for low-resource languages. |
| Approach: | They propose to use low-order statistical functions to shape model distributions for semi-supervised learning on low-resource datasets. |
| Outcome: | The proposed method improves POS and LAS on 5 target languages and provides significant gains over strong cross-lingual-transfer-plus-fine-tuning baselines for modest amounts of label data. |
Neural Cross-Lingual Named Entity Recognition with Minimal Resources (D18-1)
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| Challenge: | Named-entity recognition (NER) models are highly dependent on large amounts of labeled data. |
| Approach: | They propose a method that finds translations based on bilingual word embeddings . they also propose 'self-attention' which allows for a degree of flexibility with respect to word order . |
| Outcome: | The proposed method achieves state-of-the-art or competitive performance on common languages with lower resource requirements than previous approaches. |
Unsupervised Cross-Lingual Transfer of Structured Predictors without Source Data (2022.naacl-main)
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| Challenge: | Recent successes of NLP systems require large amounts of labelled data for structured prediction tasks. |
| Approach: | They propose a method for unsupervised transfer from multiple input models for structured prediction using a cross-lingual setup. |
| Outcome: | The proposed method produces less noisy labels for the distant supervision. |