Research map / Graph learning / Graph self-supervised learning
A Graph Convolutional Network with Adaptive Graph Generation and Channel Selection for Event Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use adaptive graph generation with gated multi-channel convolution | AGGED · ACE2005 test | F1: 78.6 -> 79.9 | Helped |
| add multi-channel selection (ablation) | AGGED · ACE2005 test | F1: 79.4 -> 79.9 | Helped |
| add information gating (ablation) | AGGED · ACE2005 test | F1: 78.7 -> 79.9 | Helped |
| add both multi-channel selection and information gating (ablation) | AGGED · ACE2005 test | F1: 79.0 -> 79.9 | Helped |
| use adaptive graph generation instead of a static dependency parse graph (ablation) | AGGED · ACE2005 test | F1: 78.3 -> 79.9 | Helped |
| pretrain the graph generator with a burn-in phase (ablation) | AGGED · ACE2005 test | F1: 77.9 -> 79.9 | Helped |
| increase the number of information channels from fewer than 3 to 3 (ablation) | AGGED · ACE2005 validation and test | F1 | Helped |
| increase the number of information channels beyond 3 (ablation) | AGGED · ACE2005 validation and test | F1 | Hurt |
Closest papers by meaning
- Graph Convolutional Networks With Argument-Aware Pooling for Event Detection (AAAI 2018 · similarity 0.89)
- Dependency Structure-Enhanced Graph Attention Networks for Event Detection (AAAI 2024 · similarity 0.87)
- A Dynamic GCN with Cross-Representation Distillation for Event-Based Learning (AAAI 2024 · similarity 0.86)
- Hierarchical and Incremental Structural Entropy Minimization for Unsupervised Social Event Detection (AAAI 2024 · similarity 0.86)
- Adaptive Graph Convolutional Neural Networks (AAAI 2018 · similarity 0.85)
- AEGNN: Asynchronous Event-Based Graph Neural Networks (CVPR 2022 · similarity 0.85)
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