Papers with pseudo labeling
Named Entity Recognition Under Domain Shift via Metric Learning for Life Sciences (2024.naacl-long)
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| Challenge: | Existing models for named entity recognition fail in scientific domains such as biomedicine and chemistry. |
| Approach: | They propose a model to transfer knowledge from the biomedical domain to the target domain . they use pseudo labeling and contrastive learning to enhance discrimination . |
| Outcome: | The proposed model outperforms baseline models by up to 5% . the proposed model is based on a biomedical domain model and a chemical domain model . |
Improving Unsupervised Out-of-domain detection through Pseudo Labeling and Learning (2023.findings-eacl)
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| Challenge: | Unsupervised OOD detection is a task aimed at discriminating whether given samples are from the in-domain (IND) . previous studies adopted the one-class classification approach, assuming that the training samples come from a single domain. |
| Approach: | They propose a framework that leverages latent categorical information to improve representation learning for textual OOD detection. |
| Outcome: | The proposed framework significantly outperforms baseline models on three datasets. |
GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval (2022.naacl-main)
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| Challenge: | Dense retrieval approaches suffer from the lexical gap and require large amounts of training data. |
| Approach: | They propose an unsupervised method for domain adaptation that uses query generator and pseudo labeling from a cross-encoder to improve retrieval performance. |
| Outcome: | The proposed method outperforms state-of-the-art retrieval methods on domain-specialized datasets by 9.3 points nDCG@10 on six tasks. |