Papers with attention masking procedure
Grouped-Attention for Content-Selection and Content-Plan Generation (2021.findings-emnlp)
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| Challenge: | Recent neural data-to-text generation models explicitly learn content-plan given a set of attributes as input. |
| Approach: | They propose a neural content-planner that captures local and global contexts . they use a token-level attention constrained within each input attribute . |
| Outcome: | The proposed model outperforms competitors by 4.92%, 4.70%, and 16.56% on real-world datasets. |