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#### 一、ACL 2019
1. **Graph Neural Networks with Generated Parameters for Relation** *Hao Zhu and Yankai Lin and Zhiyuan Liu, Jie Fu, Tat-seng Chua, Maosong Sun*
https://arxiv.org/pdf/1902.00756.pdf
2. **Entity-Relation Extraction as Multi-turn Question Answering** *Xiaoya Li, Fan Yin, Zijun Sun, Xiayu Li Arianna Yuan, Duo Chai, Mingxin Zhou and Jiwei Li*
https://arxiv.org/abs/1905.05529
3. **Matching the Blanks: Distributional Similarity for Relation Learning** *Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, Tom Kwiatkowski*
https://arxiv.org/abs/1905.05529
4. **Exploiting Entity BIO Tag Embeddings and Multi-task Learning for Relation Extraction with Imbalanced Data**
https://arxiv.org/pdf/1906.08931.pdf
5. **GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction** *Tsu-Jui Fu, Peng-Hsuan Li and Wei-Yun Ma*
https://tsujuifu.github.io/pubs/acl19_graph-rel.pdf
6. **DocRED: A Large-Scale Document-Level Relation Extraction Dataset** *Yuan Yao, Deming Ye, Peng Li, Xu Han, Yankai Lin, Zhenghao Liu, Zhiyuan Liu, Lixin Huang, Jie Zhou, Maosong Sun*
https://www.aclweb.org/anthology/P19-1074
7. **Attention Guided Graph Convolutional Networks for Relation Extraction** *Zhijiang Guo, Yan Zhang and Wei Lu*
https://www.aclweb.org/anthology/P19-1024.pdf
8. **Neural Relation Extraction for Knowledge Base Enrichment** *Bayu Distiawan Trisedya, Gerhard Weikum, Jianzhong Qi, Rui Zhang*
https://www.aclweb.org/anthology/P19-1023.pdf
9. **Joint Type Inference on Entities and Relations via Graph Convolutional Networks** *Changzhi Sun, Yeyun Gong, Yuanbin Wu, Ming Gong, Daxin Jiang, Man Lan, Shiliang Sun, Nan Duan*
https://pdfs.semanticscholar.org/7ce8/ce2768907421fb1a6cbfe13a8a36992721a7.pdf
二、AAAI 2019
1. **Hybrid Attention-based Prototypical Networks for Noisy Few-Shot Relation Classification** *Tianyu Gao, Xu Han, Zhiyuan Liu, Maosong Sun.*
https://gaotianyu1350.github.io/assets/aaai2019_hatt_paper.pdf
2. **A Hierarchical Framework for Relation Extraction with Reinforcement Learning** *Takanobu, Ryuichi and Zhang, Tianyang and Liu, Jiexi and Huang, Minlie*
https://arxiv.org/pdf/1811.03925.pdf
3. **Kernelized Hashcode Representations for Biomedical Relation Extraction** *Sahil Garg, Aram Galstyan, Greg Ver Steeg Irina Rish, Guillermo Cecchi, Shuyang Gao*
https://arxiv.org/pdf/1711.04044.pdf
4. **Cross-relation Cross-bag Attention for Distantly-supervised Relation Extraction** *Yujin Yuan, Liyuan Liu, Siliang Tang, Zhongfei Zhang, Yueting Zhuang, Shiliang Pu, Fei Wu, Xiang Ren*
https://arxiv.org/pdf/1812.10604.pdf
#### 三、NAACL 2019
1. **Structured Minimally Supervised Learning for Neural Relation Extraction** *Fan Bai and Alan Ritter*
https://arxiv.org/pdf/1904.00118.pdf
2. **Combining Distant and Direct Supervision for Neural Relation Extraction** *Iz Beltagy, Kyle Lo and Waleed Ammar*
https://arxiv.org/pdf/1810.12956.pdf
3. **Distant Supervision Relation Extraction with Intra-Bag and Inter-Bag Attentions** *Ye, Zhi-Xiu and Ling, Zhen-Hua*
https://www.aclweb.org/anthology/N19-1288
4. **A Richer-but-Smarter Shortest Dependency Path with Attentive Augmentation for Relation Extraction** *Duy-Cat Can, Hoang-Quynh Le, Quang-Thuy Ha, Nigel Collier*
https://www.aclweb.org/anthology/N19-1298
5. **Connecting Language and Knowledge with Heterogeneous Representations for Neural Relation Extraction** *Peng Xu and Denilson Barbosa*
https://arxiv.org/abs/1903.10126
6. **GAN Driven Semi-distant Supervision for Relation Extraction** *Pengshuai Li, Xinsong Zhang, Weijia Jia, Hai Zhao*
https://www.aclweb.org/anthology/N19-1307
7. **Exploiting Noisy Data in Distant Supervision Relation Classification** *Kaijia Yang, Liang He, Xin-yu Dai, Shujian Huang, Jiajun Chen*
https://www.aclweb.org/anthology/N19-1325
8. **Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks** *Ningyu Zhang, Shumin Deng, Zhanlin Sun,Guanying Wang, Xi Chen, Wei Zhang, Huajun Chen*
https://www.aclweb.org/anthology/N19-1306
#### Reference
https://github.com/WindChimeRan/NREPapers2019

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#### 2020
1. **Cross-media Structured Common Space for Multimedia Event Extraction** Manling Li, Alireza Zareian, Qi Zeng, Spencer Whitehead, Di Lu, Heng Ji and Shih-Fu Chang
https://arxiv.org/pdf/2005.02472.pdf
2. **Document-Level Event Role Filler Extraction using Multi-Granularity Contextualized Encoding** Xinya Du and Claire Cardie
https://arxiv.org/abs/2005.06579
3. **Improving Event Detection via Open-domain Trigger Knowledge** Meihan Tong, Bin Xu, Shuai Wang, Yixin Cao, Lei Hou, Juanzi Li and Jun Xie
4. **A Two-Step Approach for Implicit Event Argument Detection** Zhisong Zhang, Xiang Kong, Zhengzhong Liu, Xuezhe Ma and Eduard Hovy
https://www.aclweb.org/anthology/W16-1618.pdf
5. **Towards Open Domain Event Trigger Identification using Adversarial Domain Adaptation** Aakanksha Naik and Carolyn Rose
#### 2019
1. [Cost-sensitive Regularization for Label Confusion-aware Event Detection](https://arxiv.org/abs/1906.06003) by Hongyu Lin, Yaojie Lu, Xianpei Han, Le Sun ([Github](https://github.com/sanmusunrise/CSR))
2. [Exploiting a More Global Context for Event Detection Through Bootstrapping](https://link.springer.com/chapter/10.1007/978-3-030-15712-8_51) by Dorian Kodelja, Romaric Besançon, Olivier Ferret
3. [Context awareness and embedding for biomedical event extraction](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btz607/5544930?redirectedFrom=fulltext) by Shankai Yan, Ka-Chun Wong
4. [Biomedical Event Extraction based on Knowledge-driven Tree-LSTM](https://www.aclweb.org/anthology/N19-1145/) by Diya Li, Lifu Huang, Heng Ji, Jiawei Han
5. [Exploiting the Ground-Truth: An Adversarial Imitation Based Knowledge Distillation Approach for Event Detection](https://aaai.org/ojs/index.php/AAAI/article/view/4649) by Jian Liu, Yubo Chen, Kang Liu
6. [Joint Entity and Event Extraction with Generative Adversarial Imitation Learning](http://nlp.cs.rpi.edu/paper/imitation2019.pdf) by Tongtao Zhang, Heng Ji, Avirup Sil
7. [Event Detection using Hierarchical Multi-Aspect Attention](https://dl.acm.org/citation.cfm?doid=3308558.3313659) by Sneha Mehta, Mohammad Raihanul Islam, Huzefa Rangwala, Naren Ramakrishnan ([Github](https://github.com/sumehta/FBMA))
8. [Extracting Entities and Events as a Single Task Using a Transition-Based Neural Model](https://www.ijcai.org/proceedings/2019/753) by Junchi Zhang, Yanxia Qin, Yue Zhang, Mengchi Liu, Donghong Ji
9. [Leveraging Multi-head Attention Mechanism to Improve Event Detection](https://link.springer.com/chapter/10.1007%2F978-3-030-32381-3_22) by Meihan Tong, Bin Xu, Lei Hou, Juanzi Li, Shuai Wang
10. [Using Mention Segmentation to Improve Event Detection with Multi-head Attention](https://ialp2019.com/files/papers/IALP2019_092.pdf) by Jiali Chen, Yu Hong, Jingli Zhang, and Jianmin Yao
11. [Distilling Discrimination and Generalization Knowledge for Event Detection via Delta-Representation Learning](https://www.aclweb.org/anthology/P19-1429/) by Yaojie Lu, Hongyu Lin, Xianpei Han, Le Sun
12. [Detecting Subevents using Discourse and Narrative Features](https://www.aclweb.org/anthology/P19-1471/) by Mohammed Aldawsari, Mark Finlayson
13. [Cost-sensitive Regularization for Label Confusion-aware Event Detection](https://www.aclweb.org/anthology/P19-1521/) by Hongyu Lin, Yaojie Lu, Xianpei Han, Le Sun
14. [Exploring Pre-trained Language Models for Event Extraction and Generation](https://www.aclweb.org/anthology/P19-1522/) by Sen Yang, Dawei Feng, Linbo Qiao, Zhigang Kan, Dongsheng Li
15. [Open Event Extraction from Online Text using a Generative Adversarial Network](https://www.aclweb.org/anthology/D19-1027/) by Rui Wang, Deyu ZHOU, Yulan He
16. [Cross-lingual Structure Transfer for Relation and Event Extraction](https://www.aclweb.org/anthology/D19-1030/) by Ananya Subburathinam, Di Lu, Heng Ji, Jonathan May, Shih-Fu Chang, Avirup Sil, Clare Voss
17. [Event Detection with Trigger-Aware Lattice Neural Network](https://www.aclweb.org/anthology/D19-1033/) by Ning Ding, Ziran Li, Zhiyuan Liu, Haitao Zheng, Zibo Lin ([Github](https://github.com/thunlp/TLNN))
18. [Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction](https://www.aclweb.org/anthology/D19-1041/) by Rujun Han, Qiang Ning, Nanyun Peng ([Github](https://github.com/rujunhan/EMNLP-2019))
19. [HMEAE: Hierarchical Modular Event Argument Extraction](https://www.aclweb.org/anthology/D19-1584/) by Xiaozhi Wang, Ziqi Wang, Xu Han, Zhiyuan Liu, Juanzi Li, Peng Li, Maosong Sun, Jie Zhou, Xiang Ren ([Github](https://github.com/thunlp/HMEAE))
20. [Entity, Relation, and Event Extraction with Contextualized Span Representations](https://www.aclweb.org/anthology/D19-1585/) by David Wadden, Ulme Wennberg, Yi Luan, Hannaneh Hajishirzi ([Github](https://github.com/dwadden/dygiepp))
#### 2018
1. [Similar but not the Same: Word Sense Disambiguation Improves Event Detection via Neural Representation Matching](https://www.aclweb.org/anthology/D18-1517/) by Weiyi Lu, Thien Huu Nguyen
2. [Exploiting Contextual Information via Dynamic Memory Network for Event Detection](https://www.aclweb.org/anthology/D18-1127/) by Shaobo Liu, Rui Cheng, Xiaoming Yu, Xueqi Cheng ([Github](https://github.com/AveryLiu/TD-DMN))
3. [Nugget Proposal Networks for Chinese Event Detection](https://www.aclweb.org/anthology/P18-1145/) by Hongyu Lin, Yaojie Lu, Xianpei Han, Le Sun ([Github](https://github.com/sanmusunrise/NPNs))
4. [Extracting Biomedical Events with Parallel Multi-Pooling Convolutional Neural Networks](https://ieeexplore.ieee.org/document/8453008) by Lishuang Li ; Yang Liu ; Meiyue Qin
5. [Jointly Extracting Event Triggers and Arguments by Dependency-Bridge RNN and Tensor-Based Argument Interaction](https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16222) by Lei Sha, Feng Qian, Baobao Chang, Zhifang Sui
6. [Learning Target-Dependent Sentence Representations for Chinese Event Detection](https://link.springer.com/chapter/10.1007/978-3-030-01012-6_20) by Wenbo Zhang, Xiao Ding, Ting Liu
7. [One for All: Neural Joint Modeling of Entities and Events](https://arxiv.org/abs/1812.00195) by Trung Minh Nguyen, Thien Huu Nguyen
8. [Empower event detection with bi-directional neural language model](https://www.sciencedirect.com/science/article/abs/pii/S0950705119300097?via%3Dihub) by Yunyan Zhang , Guangluan Xu , Yang Wang, Xiao Liang, Lei Wang, Tinglei Huang
9. [Jointly Multiple Events Extraction via Attention-based Graph Information Aggregation](https://arxiv.org/abs/1809.09078) by Xiao Liu, Zhunchen Luo, Heyan Huang ([Github](https://github.com/lx865712528/EMNLP2018-JMEE))
10. [Graph Convolutional Networks With Argument-Aware Pooling for Event Detection](https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16329) by Thien Huu Nguyen, Ralph Grishman
11. [Chinese Event Recognition via Ensemble Model](https://link.springer.com/chapter/10.1007%2F978-3-030-04221-9_23) by Wei Liu, Zhenyu Yang, Zongtian Liu
12. [A neural network based Event extraction system for Indian languages](http://ceur-ws.org/Vol-2266/T5-2.pdf) by Alapan Kuila, Sarath chandra Bussa, Sudeshna Sarkar
13. [5W1H Information Extraction with CNN-Bidirectional LSTM](https://iopscience.iop.org/article/10.1088/1742-6596/978/1/012078) by A Nurdin1, N U Maulidevi
14. [Self-regulation: Employing a Generative Adversarial Network to Improve Event Detection](https://www.aclweb.org/anthology/P18-1048/) by Yu Hong, Wenxuan Zhou, Jingli Zhang, Guodong Zhou, Qiaoming Zhu ([Github](https://github.com/JoeZhouWenxuan/Self-regulation-Employing-a-Generative-Adversarial-Network-to-Improve-Event-Detection))
15. [Event Detection via Recurrent Neural Networkand Argument Prediction](http://tcci.ccf.org.cn/conference/2018/papers/51.pdf) by Wentao Wu, Xiaoxu Zhu, Jiaming Tao, and Peifeng Li
16. [Event Detection with Neural Networks: A Rigorous Empirical Evaluation](https://arxiv.org/abs/1808.08504) by J. Walker Orr, Prasad Tadepalli, Xiaoli Fern
17. [Using Entity Relation to Improve Event Detection via Attention Mechanism](https://link.springer.com/chapter/10.1007/978-3-319-99495-6_15) by Jingli Zhang, Wenxuan Zhou, Yu Hong, Jianmin Yao, Min Zhang
18. [Event Extraction with Deep Contextualized Word Representation and Multi-attention Layer](https://link.springer.com/chapter/10.1007/978-3-030-05090-0_17) by Ruixue Ding, Zhoujun Li
19. [Chinese Event Extraction Based on Attention and Semantic Features: A Bidirectional Circular Neural Network](https://www.mdpi.com/1999-5903/10/10/95) by Yue Wu; Junyi Zhang20. [Document Embedding Enhanced Event Detection with Hierarchical and Supervised Attention](https://www.aclweb.org/anthology/P18-2066/) by Yue Zhao, Xiaolong Jin, Yuanzhuo Wang, Xueqi Cheng
21. [Collective Event Detection via a Hierarchical and Bias Tagging Networks with Gated Multi-level Attention Mechanisms](https://www.aclweb.org/anthology/D18-1158/) by Yubo Chen, Hang Yang, Kang Liu, Jun Zhao, Yantao Jia
22. [Event Detection via Gated Multilingual Attention Mechanism](http://www.nlpr.ia.ac.cn/cip/~liukang/liukangPageFile/Liu_aaai2018.pdf) by Jian Liu, Yubo Chen1, Kang Liu, Jun Zhao
23. [Prior Knowledge Integrated with Self-attention for Event Detection](https://link.springer.com/chapter/10.1007/978-3-030-01012-6_21) by Yan Li, Chenliang Li, Weiran Xu, Junliang Li
#### Reference
https://github.com/WindChimeRan/NREPapers2019#naacl-2019