Papers with fully-interpretable reasoning paths
Towards Large-Scale Interpretable Knowledge Graph Reasoning for Dialogue Systems (2022.findings-acl)
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| Challenge: | Existing systems that require extensive labor to process user requests are limited in their reasoning capabilities and require extensive manual effort to design. |
| Approach: | They propose a method that allows a transformer model to walk on a large-scale knowledge graph to generate responses by reasoning over differentiable knowledge graphs. |
| Outcome: | The proposed method allows a transformer model to walk on a large-scale knowledge graph to generate responses. |