Papers with semantic self-attention layer
Cascaded Semantic and Positional Self-Attention Network for Document Classification (2020.findings-emnlp)
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| Challenge: | Existing approaches to document classification combine semantic information with positional information (word orders) . document classification is one of the fundamental problems in natural language processing . |
| Approach: | They propose a new architecture to combine semantic and positional information using a semantic self-attention layer cascaded with Bi-LSTM. |
| Outcome: | The proposed model can exploit the interaction between semantics and word positions in a more interpretable and adaptive manner while preserving a compact model size and high convergence rate. |