Papers with generative or information compression models
Span-based Named Entity Recognition by Generating and Compressing Information (2023.eacl-main)
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| Challenge: | Existing work on Named Entity Recognition (NER) only used generative or information compression models to improve performance. |
| Approach: | They propose to combine two types of IB models into one system to enhance Named Entity Recognition (NER) they incorporate unsupervised generative components span reconstruction and synonym generation into a span-based NER system. |
| Outcome: | The proposed model focuses on learning span representation, which is applicable not only to span-based NER but also to other span-related tasks such as event coreference resolution and question answering. |