| Challenge: | Existing work on hierarchical structure in neural networks has not captured human intuitions about hierarchic structures. |
| Approach: | They propose to add an extra constraint to attention heads of the bidirectional Transformer encoder to encourage attention heads to follow tree structures. |
| Outcome: | The proposed model improves language modeling and learning more explainable attention scores. |
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| Challenge: | Recent research has focused on sentence representations. |
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Syntax-Based Attention Masking for Neural Machine Translation (2021.naacl-srw)
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Do Syntax Trees Help Pre-trained Transformers Extract Information? (2021.eacl-main)
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Going “Deeper”: Structured Sememe Prediction via Transformer with Tree Attention (2022.findings-acl)
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