Research map / Graph learning / Knowledge and temporal graphs
Neural Knowledge Acquisition via Mutual Attention Between Knowledge Graph and Text
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| joint training with KG model (Prob-TransD) and knowledge-based attention | CNN relation extractor · NYT-FB60K | P@N mean: 61.5 -> 71.0 | Helped |
| joint learning with KG (ablation) | CNN+ONE · NYT-FB60K | P@N mean: 56.4 -> 62.6 | Helped |
| replace sentence-level attention with knowledge-based attention (ablation) | JointD · NYT-FB60K | P@N mean: 67.7 -> 71.0 | Helped |
| use Prob-TransD instead of Prob-TransE as KG model (ablation) | Joint+KATT · NYT-FB60K | P@N mean: 68.9 -> 71.0 | Helped |
| joint learning with text via semantics-based attention (ablation) | Prob-TransE · FB15K | Hits@10: 76.6 -> 79.3 | Helped |
| joint learning with text via semantics-based attention (ablation) | Prob-TransD · FB15K | Hits@10: 78.2 -> 80.4 | Helped |
| JointD+SATT vs dependency-parsing joint model | KGC · FB15K-237 | Hits@10: 61.1 -> 69.9 | Helped |
Closest papers by meaning
- Select and Augment: Enhanced Dense Retrieval Knowledge Graph Augmentation (Abstract Reprint) (AAAI 2024 · similarity 0.87)
- KGGen: Extracting Knowledge Graphs from Plain Text with Language Models (NeurIPS 2025 · similarity 0.86)
- Knowledge Graph Completion with Relation-Aware Anchor Enhancement (AAAI 2025 · similarity 0.86)
- Replacing Paths with Connection-Biased Attention for Knowledge Graph Completion (AAAI 2025 · similarity 0.85)
- KGCRR: An Effective Metric-Driven Knowledge Graph Completion Framework by Designing a Novel Upper Bound Function with Adaptive Approximation to Reciprocal Rank (AAAI 2025 · similarity 0.85)
- Mixed Geometry Message and Trainable Convolutional Attention Network for Knowledge Graph Completion (AAAI 2024 · similarity 0.85)
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