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Data scarcity has been the main factor that hinders the progress of event extraction.
Roberta: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Pseudo-labeling and confirmation bias in deep semi-supervised learning
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O’Connor, and Kevin McGuinness. 2019 · 1908
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DEGREE: A data-efficient generation-based event extraction model
I-Hung Hsu, Kuan-Hao Huang, Elizabeth Boschee, Scott Miller, Prem Natarajan, Kai-Wei Chang, and Nanyun Peng. 2022 · 1908
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J. Williams. 1992 · 1992
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Unsupervised word sense disambiguation rivaling supervised methods
David Yarowsky. 1995 · 1995
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Policy gradient methods for reinforcement learning with function approximation
Richard S. Sutton, David A. McAllester, Satinder Singh, and Yishay Mansour. 1999 · 1999
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Conditional random fields: Probabilistic models for segmenting and labeling sequence data
John D. Lafferty, Andrew McCallum, and Fernando Pereira. 2001 · 2001
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Hieu Pham, Qizhe Xie, Zihang Dai, and Quoc V. Le. 2020 · 2003
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Learning extraction patterns for subjective expressions
Ellen Riloff and Janyce Wiebe. 2003 · 2003
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Predicting good probabilities with supervised learning
Alexandru Niculescu-Mizil and Rich Caruana. 2005 · 2005
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Improved noisy student training for automatic speech recognition
Daniel S. Park, Yu Zhang, Ye Jia, Wei Han, Chung-Cheng Chiu, Bo Li, Yonghui Wu, and Quoc V. Le. 2020 · 2005
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Semi-supervised self-training of object detection models
Chuck Rosenberg, Martial Hebert, and Henry Schneiderman. 2005 · 2005
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Effective self-training for parsing
David McClosky, Eugene Charniak, and Mark Johnson. 2006 · 2006
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Refining event extraction through cross-document inference
Heng Ji and Ralph Grishman. 2008 · 2008
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Self-training for biomedical parsing
David McClosky and Eugene Charniak. 2008 · 2008
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Can one language bootstrap the other: a case study on event extraction
Zheng Chen and Heng Ji. 2009 · 2009
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Filtered ranking for bootstrapping in event extraction
Shasha Liao and Ralph Grishman. 2010 · 2010
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Can document selection help semi-supervised learning? A case study on event extraction
Shasha Liao and Ralph Grishman. 2011b · 2011
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Event extraction as dependency parsing
D. McClosky, M. Surdeanu, and C. D. Manning. 2011 · 2011
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Bootstrapped training of event extraction classifiers
Ruihong Huang and Ellen Riloff. 2012 · 2012
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Abstract meaning representation for sembanking
Laura Banarescu, Claire Bonial, Shu Cai, Madalina Georgescu, Kira Griffitt, Ulf Hermjakob, Kevin Knight, Philipp Koehn, Martha Palmer, and Nathan Schneider. 2013 · 2013
Cited alongside, same era.
Joint event extraction via structured prediction with global features
Qi Li, Heng Ji, and Liang Huang. 2013 · 2013
Cited alongside, same era.
Employing event inference to improve semi-supervised chinese event extraction
Peifeng Li, Qiaoming Zhu, and Guodong Zhou. 2014 · 2014
Cited alongside, same era.
Event extraction via dynamic multi-pooling convolutional neural networks
Y. Chen, L. Xu, K. Liu, D. Zeng, and J. Zhao. 2015 · 2015
Cited alongside, same era.
A language-independent neural network for event detection
Xiaocheng Feng, Lifu Huang, Duyu Tang, Bing Qin, Heng Ji, and Ting Liu. 2016 · 2016
Cited alongside, same era.
Liberal event extraction and event schema induction
Event extraction by answering (almost) natural questions
Xinya Du and Claire Cardie. 2020 · 2020
Later among the works it cites.
Cold-start universal information extraction
Lifu Huang. 2020 · 2020
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Semi-supervised new event type induction and event detection
Lifu Huang and Heng Ji. 2020 · 2020
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Self-training for end-to-end speech recognition
Jacob Kahn, Ann Lee, and Awni Hannun. 2020 · 2020
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A joint neural model for information extraction with global features
Ying Lin, Heng Ji, Fei Huang, and Lingfei Wu. 2020 · 2020
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Ontoed: Low-resource event detection with ontology embedding
Shumin Deng, Ningyu Zhang, Luoqiu Li, Chen Hui, Tou Huaixiao, Mosha Chen, Fei Huang, and Huajun Chen. 2021 · 2021
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Lifu Huang, Taylor Cassidy, Xiaocheng Feng, Heng Ji, Clare Voss, Jiawei Han, and Avirup Sil. 2016 · 2016
Cited alongside, same era.
Joint event extraction via recurrent neural networks
Thien Huu Nguyen, Kyunghyun Cho, and Ralph Grishman. 2016 · 2016
Cited alongside, same era.
On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q. Weinberger. 2017 · 2017
Cited alongside, same era.
Biomedical event extraction using Abstract Meaning Representation
Sudha Rao, Daniel Marcu, Kevin Knight, and Hal Daumé III. 2017 · 2017
Cited alongside, same era.
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola. 2017 · 2017
Cited alongside, same era.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Semi-supervised event extraction with paraphrase clusters
James Ferguson, Colin Lockard, Daniel S Weld, and Hannaneh Hajishirzi. 2018a · 2018
Cited alongside, same era.
Self-training improves pre-training for natural language understanding
Jingfei Du, Edouard Grave, Beliz Gunel, Vishrav Chaudhary, Onur Celebi, Michael Auli, Veselin Stoyanov, and Alexis Conneau. 2021 · 2021
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Semi-supervised relation extraction via incremental meta self-training
Xuming Hu, Chenwei Zhang, Fukun Ma, Chenyao Liu, Lijie Wen, and Philip S. Yu. 2021a · 2021
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Gradient imitation reinforcement learning for low resource relation extraction
Xuming Hu, Chenwei Zhang, Yawen Yang, Xiaohe Li, Li Lin, Lijie Wen, and Philip S. Yu. 2021b · 2021
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Abstract meaning representation (amr) annotation release 3.0
Kevin Knight, Bianca Badarau, Laura Baranescu, Claire Bonial, Madalina Bardocz, Kira Griffitt, Ulf Hermjakob, Daniel Marcu, Martha Palmer, Tim O’Gorman, et al. 2021 · 2021
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Noisy-labeled NER with confidence estimation
Kun Liu, Yao Fu, Chuanqi Tan, Mosha Chen, Ningyu Zhang, Songfang Huang, and Sheng Gao. 2021 · 2021
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Text2Event: Controllable sequence-to-structure generation for end-to-end event extraction
Yaojie Lu, Hongyu Lin, Jin Xu, Xianpei Han, Jialong Tang, Annan Li, Le Sun, Meng Liao, and Shaoyi Chen. 2021 · 2021
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Cross-task instance representation interactions and label dependencies for joint information extraction with graph convolutional networks
Minh Van Nguyen, Viet Lai, and Thien Huu Nguyen. 2021 · 2021
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Meta self-training for few-shot neural sequence labeling
Yaqing Wang, Subhabrata Mukherjee, Haoda Chu, Yuancheng Tu, Ming Wu, Jing Gao, and Ahmed Hassan Awadallah. 2021a · 2021
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CLEVE: contrastive pre-training for event extraction
Ziqi Wang, Xiaozhi Wang, Xu Han, Yankai Lin, Lei Hou, Zhiyuan Liu, Peng Li, Juanzi Li, and Jie Zhou. 2021b · 2021
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Improved latent tree induction with distant supervision via span constraints
Zhiyang Xu, Andrew Drozdov, Jay-Yoon Lee, Tim O’Gorman, Subendhu Rongali, Dylan Finkbeiner, Shilpa Suresh, Mohit Iyyer, and Andrew McCallum. 2021 · 2021
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Abstract meaning representation guided graph encoding and decoding for joint information extraction
Zixuan Zhang and Heng Ji. 2021 · 2021
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Unified structure generation for universal information extraction
Yaojie Lu, Qing Liu, Dai Dai, Xinyan Xiao, Hongyu Lin, Xianpei Han, Le Sun, and Hua Wu. 2022 · 2022
Closest in time.
Joint extraction of entities, relations, and events via modeling inter-instance and inter-label dependencies
Minh Van Nguyen, Bonan Min, Franck Dernoncourt, and Thien Nguyen. 2022 · 2022
Closest in time.
Query and extract: Refining event extraction as type-oriented binary decoding
Sijia Wang, Mo Yu, Shiyu Chang, Lichao Sun, and Lifu Huang. 2022 · 2022
Closest in time.