【论文解读 EMNLP 2019 | MOGANED】ED with Multi-Order Graph Convolution and Aggregated Attention

时间 2021-01-02

标签论文 NE&GNN 事件抽取繁體版

原文原文链接

论文题目：Event Detection with Multi-Order Graph Convolution and Aggregated Attention 论文来源：EMNLP 2019 论文链接：https://www.aclweb.org/anthology/D19-1582/ 代码链接（非官方）：https://github.com/wzq016/MOGANED-Implementat

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1. 【论文解读 EMNLP 2018 | JMEE】Jointly Multiple EE via Attention-based Graph Information Aggregation
2. 【论文解读 EMNLP 2019 | TLNN】Event Detection with Trigger-Aware Lattice Neural Network
3. 【论文解读 EMNLP 2019】Joint Event and Temporal RE with Shared Representations and Structured Prediction
4. 【论文解读 EMNLP 2019 | HMEAE】Hierarchical Modular Event Argument Extraction
5. 【论文解读 arXiv 2020 | RA-GCN】Event Detection with Relation-Aware Graph Convolutional Networks
6. 《Heterogeneous Graph Attention Network》论文解读
7. 【论文笔记】：Object detection with location-aware deformable convolution and backward attention filtering
8. 【论文解读 AAAI 2018|GCN-ED】Graph Convolutional Networks with Argument-Aware Pooling for Event Detection
9. 【论文解读 WWW 2019 | HAN】Heterogeneous Graph Attention Network
10. 《GRAPH ATTENTION NETWORKS》论文理解

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