ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge Graph (2023.emnlp-main)
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| Challenge: | Question Answering over Knowledge Graph (KGQA) aims to find answer entities for natural language questions based on knowledge graphs. |
| Approach: | They propose a subgraph-aware self-attention mechanism to imitate the graph neural network (GNN) based module to perform multi-hop reasoning on KG. |
| Outcome: | The proposed method surpasses state-of-the-art models by a large margin even with fewer updated parameters and less training data. |
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