EXPLAIGNN (Christmann et al., 2023) constructs a heterogeneous graph from retrieved knowledge and user explanations to trace provenance and improve answer explainability, generating explanatory evidence using a graph neural network (GNN) with question-level attention.

Authors

• Person: Not available Organization: arXiv
  Large Language Models Meet Knowledge Graphs for Question ...

Sources

• Large Language Models Meet Knowledge Graphs for Question ... arxiv.org arXiv via serper

Referenced by nodes (2)

• graph neural networks concept
• provenance concept