Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning
We focus on graph-to-sequence learning, which can be framed as transducing graph structures to sequences for text generation. To capture structural information associated with graphs, we investigate the problem of encoding graphs using graph convolutional networks (GCNs). Unlike various existing app...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The MIT Press
2019-11-01
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| Series: | Transactions of the Association for Computational Linguistics |
| Online Access: | https://www.mitpressjournals.org/doi/abs/10.1162/tacl_a_00269 |