Research map / Graph learning / Knowledge and temporal graphs
Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use bidirectional self-attention over the query | BiQE · FB15K-237-CQ | MRR: 0.157 -> 0.228 | Helped |
| use bidirectional self-attention over the query | BiQE · WN18RR-CQ | MRR: 0.149 -> 0.150 | Helped |
| use bidirectional self-attention over the query | BiQE · Bio | AUC: 91.0 -> 96.91 | Helped |
| remove attention to future query context (ablation) | BiQE · FB15K-237-Paths | MRR: 0.473 -> 0.421 | Hurt |
| remove attention to future query context (ablation) | BiQE · FB15K-237-Paths | HITS@10: 0.602 -> 0.553 | Hurt |
| double GQE embedding dimensions (ablation) | GQE · FB15K-237 and NELL-995 | HITS@3 (Mean): 0.246 -> 0.249; 0.269 -> 0.270 | No clear effect |
| answer missing entities jointly rather than one at a time (ablation) | BiQE · FB15K-237-Paths | MRR: 0.421 -> 0.473 | Helped |
| answer missing entities jointly rather than one at a time (ablation) | BiQE · FB15K-237-Paths | HITS@10: 0.553 -> 0.602 | Helped |
Closest papers by meaning
- Query Embedding on Hyper-Relational Knowledge Graphs (ICLR 2022 · similarity 0.89)
- NQE: N-ary Query Embedding for Complex Query Answering over Hyper-Relational Knowledge Graphs (AAAI 2023 · similarity 0.88)
- Harnessing Large Language Models for Knowledge Graph Question Answering via Adaptive Multi-Aspect Retrieval-Augmentation (AAAI 2025 · similarity 0.86)
- Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors (ICLR 2024 · similarity 0.85)
- Replacing Paths with Connection-Biased Attention for Knowledge Graph Completion (AAAI 2025 · similarity 0.85)
- Context-aware Inductive Knowledge Graph Completion with Latent Type Constraints and Subgraph Reasoning (AAAI 2025 · similarity 0.85)
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