Papers by Jewgeni Rose
Space Efficient Context Encoding for Non-Task-Oriented Dialogue Generation with Graph Attention Transformer (2021.acl-long)
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| Challenge: | Recent Transformer-based models aim to integrate fixed background context into non-task-oriented dialogue systems, but the context length is fixed in these architectures, which restricts how much background or dialogue context can be kept. |
| Approach: | They propose a more concise encoding for background context structured in the form of knowledge graphs by expressing the graph connections through restrictions on the attention weights. |
| Outcome: | The proposed architecture reduces space requirements without negative effects on the precision of reproduction of knowledge and perceived consistency. |