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Event detection refers to identifying event occurrences in a text and comprises of two subtasks; event identification and classification.
Codesearchnet challenge: Evaluating the state of semantic code search
Hamel Husain, Hongqi Wu, Tiferet Gazit, Miltiadis Allamanis, and Marc Brockschmidt. 2019 · 1909
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Extending event detection to new types with learning from keywords
Viet Dac Lai and Thien Huu Nguyen. 2019 · 1910
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Multitask learning
Rich Caruana. 1997 · 1997
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The stages of event extraction
David Ahn. 2006 · 2006
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Refining event extraction through cross-document inference
Heng Ji and Ralph Grishman. 2008 · 2008
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Predicting unknown time arguments based on cross-event propagation
Prashant Gupta and Heng Ji. 2009 · 2009
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A unified model of phrasal and sentential evidence for information extraction
Siddharth Patwardhan and Ellen Riloff. 2009 · 2009
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Character-level analysis of semi-structured documents for set expansion
Richard C. Wang and William W. Cohen. 2009 · 2009
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Event detection: Gate diversity and syntactic importance scoresfor graph convolution neural networks
Viet Dac Lai, Tuan Ngo Nguyen, and Thien Huu Nguyen. 2020b · 2010
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Using document level cross-event inference to improve event extraction
Shasha Liao and Ralph Grishman. 2010 · 2010
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Using cross-entity inference to improve event extraction
Yu Hong, Jianfeng Zhang, Bin Ma, Jianmin Yao, Guodong Zhou, and Qiaoming Zhu. 2011 · 2011
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Acquiring topic features to improve event extraction: in pre-selected and balanced collections
Shasha Liao and Ralph Grishman. 2011 · 2011
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Event extraction as dependency parsing
David McClosky, Mihai Surdeanu, and Christopher Manning. 2011 · 2011
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Fast and robust joint models for biomedical event extraction
Sebastian Riedel and Andrew McCallum. 2011a · 2011
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Robust biomedical event extraction with dual decomposition and minimal domain adaptation
Sebastian Riedel and Andrew McCallum. 2011b · 2011
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Joint modeling for chinese event extraction with rich linguistic features
Chen Chen and Vincent Ng. 2012 · 2012
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Event extraction across multiple levels of biological organization
Sampo Pyysalo, Tomoko Ohta, Makoto Miwa, Han-Cheol Cho, Jun’ichi Tsujii, and Sophia Ananiadou. 2012 · 2012
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Distributional semantics resources for biomedical text processing
S Pyysalo, F Ginter, H Moen, T Salakoski, and S Ananiadou. 2013 · 2013
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Dependency-based word embeddings
Omer Levy and Yoav Goldberg. 2014 · 2014
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Relieving the computational bottleneck: Joint inference for event extraction with high-dimensional features
Deepak Venugopal, Chen Chen, Vibhav Gogate, and Vincent Ng. 2014 · 2014
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Seed-based event trigger labeling: How far can event descriptions get us?
Ofer Bronstein, Ido Dagan, Qi Li, Heng Ji, and Anette Frank. 2015 · 2015
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Event extraction via dynamic multi-pooling convolutional neural networks
Yubo Chen, Liheng Xu, Kang Liu, Daojian Zeng, and Jun Zhao. 2015 · 2015
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Contextual code completion using machine learning
Subhasis Das. 2015 · 2015
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Event detection and domain adaptation with convolutional neural networks
Thien Huu Nguyen and Ralph Grishman. 2015 · 2015
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Embedding assisted prediction architecture for event trigger identification
Yifan Nie, Wenge Rong, Yiyuan Zhang, Yuanxin Ouyang, and Zhang Xiong. 2015 · 2015
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A semi-supervised learning framework for biomedical event extraction based on hidden topics
Deyu Zhou and Dayou Zhong. 2015 · 2015
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Deepcoder: Learning to write programs
Matej Balog, Alexander L Gaunt, Marc Brockschmidt, Sebastian Nowozin, and Daniel Tarlow. 2016 · 2016
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Event nugget detection with forward-backward recurrent neural networks
Reza Ghaeini, Xiaoli Fern, Liang Huang, and Prasad Tadepalli. 2016 · 2016
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Temporal information retrieval
Nattiya Kanhabua and Avishek Anand. 2016 · 2016
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A probabilistic soft logic based approach to exploiting latent and global information in event classification
Shulin Liu, Kang Liu, Shizhu He, and Jun Zhao. 2016 · 2016
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Joint event extraction via recurrent neural networks
Thien Huu Nguyen, Kyunghyun Cho, and Ralph Grishman. 2016 · 2016
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Learning to represent programs with graphs
Miltiadis Allamanis, Marc Brockschmidt, and Mahmoud Khademi. 2017 · 2017
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Automatically labeled data generation for large scale event extraction
Yubo Chen, Shulin Liu, Xiang Zhang, Kang Liu, and Jun Zhao. 2017 · 2017
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Code completion with neural attention and pointer networks
Jian Li, Yue Wang, Michael R Lyu, and Irwin King. 2017 · 2017
Cited alongside, same era.
Exploiting argument information to improve event detection via supervised attention mechanisms
Shulin Liu, Yubo Chen, Kang Liu, and Jun Zhao. 2017 · 2017
Cited alongside, same era.
Biomedical event trigger identification using bidirectional recurrent neural network based models
Rahul V S S Patchigolla, Sunil Sahu, and Ashish Anand. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
A multiple distributed representation method based on neural network for biomedical event extraction
Anran Wang, Jian Wang, Hongfei Lin, Jianhai Zhang, Zhihao Yang, and Kan Xu. 2017 · 2017
Cited alongside, same era.
MAVEN: A Massive General Domain Event Detection Dataset
Xiaozhi Wang, Ziqi Wang, Xu Han, Wangyi Jiang, Rong Han, Zhiyuan Liu, Juanzi Li, Peng Li, Yankai Lin, and Jie Zhou. 2020 · 2020
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Event detection as question answering with entity information
Emanuela Boros, José G. Moreno, and Antoine Doucet. 2021 · 2021
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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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Empirical analysis on effectiveness of nlp methods for predicting code smell
Himanshu Gupta, Abhiram Anand Gulanikar, Lov Kumar, and Lalita Bhanu Murthy Neti. 2021a · 2021
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Peter Hase and Mohit Bansal. 2021 · 2021
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code2vec: learning distributed representations of code
Uri Alon, Meital Zilberstein, Omer Levy, and Eran Yahav. 2018 · 2018
Cited alongside, same era.
Implicit argument prediction with event knowledge
Pengxiang Cheng and Katrin Erk. 2018 · 2018
Cited alongside, same era.
Biomedical event trigger detection based on bilstm integrating attention mechanism and sentence vector
Xinyu He, Lishuang Li, Jia Wan, Dingxin Song, Jun Meng, and Zhanjie Wang. 2018b · 2018
Cited alongside, same era.
Jointly multiple events extraction via attention-based graph information aggregation
Xiao Liu, Zhunchen Luo, and Heyan Huang. 2018 · 2018
Cited alongside, same era.
seqeval: A python framework for sequence labeling evaluation
Hiroki Nakayama. 2018 · 2018
Cited alongside, same era.
Jointly extracting event triggers and arguments by dependency-bridge rnn and tensor-based argument interaction
Lei Sha, Feng Qian, Baobao Chang, and Zhifang Sui. 2018 · 2018
Cited alongside, same era.
Neural-guided deductive search for real-time program synthesis from examples
Ashwin J. Vijayakumar, Abhishek Mohta, Oleksandr Polozov, Dhruv Batra, Prateek Jain, and Sumit Gulwani. 2018 · 2018
Cited alongside, same era.
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Modeling textual cohesion for event extraction
Ruihong Huang and Ellen Riloff. 2021 · 2021
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Document-level event argument extraction by conditional generation
Sha Li, Heng Ji, and Jiawei Han. 2021 · 2021
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Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2021 · 2021
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Unicorn on rainbow: A universal commonsense reasoning model on a new multitask benchmark
Nicholas Lourie, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 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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Zero-shot event extraction via transfer learning: Challenges and insights
Qing Lyu, Hongming Zhang, Elior Sulem, and Dan Roth. 2021 · 2021
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Structured prediction as translation between augmented natural languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, Rishita Anubhai, Cicero Nogueira dos Santos, Bing Xiang, and Stefano Soatto. 2021 · 2021
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Multitask prompted training enables zero-shot task generalization
Victor Sanh, Albert Webson, Colin Raffel, Stephen H Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, et al. 2021 · 2021
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Unleash gpt-2 power for event detection
Amir Pouran Ben Veyseh, Viet Dac Lai, Franck Dernoncourt, and Thien Huu Nguyen. 2021 · 2021
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Query and extract: Refining event extraction as type-oriented binary decoding
Sijia Wang, Mo Yu, Shiyu Chang, Lichao Sun, and Lifu Huang. 2021 · 2021
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Learning to generate task-specific adapters from task description
Qinyuan Ye and Xiang Ren. 2021 · 2021
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Zero-shot Label-aware Event Trigger and Argument Classification
Hongming Zhang, Haoyu Wang, and Dan Roth. 2021 · 2021
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Ethical-advice taker: Do language models understand natural language interventions?
Jieyu Zhao, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, and Kai-Wei Chang. 2021 · 2021
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Adapting language models for zero-shot learning by meta-tuning on dataset and prompt collections
Ruiqi Zhong, Kristy Lee, Zheng Zhang, and Dan Klein. 2021 · 2021
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A biomedical event extraction method based on fine-grained and attention mechanism
Xinyu He, Ping Tai, Hongbin Lu, Xin Huang, and Yonggong Ren. 2022 · 2022
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Prediction of students’ performance with artificial neural network using demographic traits
Adeniyi Jide Kehinde, Abidemi Emmanuel Adeniyi, Roseline Oluwaseun Ogundokun, Himanshu Gupta, and Sanjay Misra. 2022 · 2022
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Saliency as evidence: Event detection with trigger saliency attribution
Jian Liu, Yufeng Chen, and Jinan Xu. 2022 · 2022
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Reframing instructional prompts to gptk’s language
Swaroop Mishra, Daniel Khashabi, Chitta Baral, Yejin Choi, and Hannaneh Hajishirzi. 2022 · 2022
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Computational intelligence approaches for heart disease detection
Roseline Oluwaseun Ogundokun, Sanjay Misra, Peter Ogirima Sadiku, Himanshu Gupta, Robertas Damasevicius, and Rytis Maskeliunas. 2022 · 2022
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In-boxbart: Get instructions into biomedical multi-task learning
Mihir Parmar, Swaroop Mishra, Mirali Purohit, Man Luo, M. Hassan Murad, and Chitta Baral. 2022 · 2022
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Generating disentangled arguments with prompts: A simple event extraction framework that works
Jinghui Si, Xutan Peng, Chen Li, Haotian Xu, and Jianxin Li. 2022 · 2022
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Super-NaturalInstructions: Generalization via declarative instructions on 1600+ NLP tasks
Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Atharva Naik, Arjun Ashok, Arut Selvan Dhanasekaran, Anjana Arunkumar, David Stap, Eshaan Pathak, Giannis Karamanolakis, Haizhi Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Kuntal Kumar Pal, Maitreya Patel, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Savan Doshi, Shailaja Keyur Sampat, Siddhartha Mishra, Sujan Reddy A, Sumanta Patro, Tanay Dixit, and Xudong Shen. 2022b · 2022
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Do prompt-based models really understand the meaning of their prompts?
Albert Webson and Ellie Pavlick. 2022 · 2022
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Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le. 2022 · 2022
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Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer, and Tao Yu. 2022 · 2022
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Event detection explorer: An interactive tool for event detection exploration
Wenlong Zhang, Bhagyashree Ingale, Hamza Shabir, Tianyi Li, Tian Shi, and Ping Wang. 2022 · 2022
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Instructabsa: Instruction learning for aspect based sentiment analysis
Kevin Scaria, Himanshu Gupta, Saurabh Arjun Sawant, Swaroop Mishra, and Chitta Baral. 2023 · 2023
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