Fetching the paper…
Reading the bibliography…
In this paper, we propose an effective yet efficient model PAIE for both sentence-level and document-level Event Argument Extraction (EAE), which also generalizes well when there is a lack of training data.
The hungarian method for the assignment problem
Harold W Kuhn. 1955 · 1955
Earlier work this paper cites.
Overview of the fourth Message Understanding Evaluation and Conference
Beth M. Sundheim. 1992 · 1992
Earlier work this paper cites.
The automatic content extraction (ACE) program – tasks, data, and evaluation
George Doddington, Alexis Mitchell, Mark Przybocki, Lance Ramshaw, Stephanie Strassel, and Ralph Weischedel. 2004 · 2004
Earlier work this paper cites.
Joint event extraction via structured prediction with global features
Qi Li, Heng Ji, and Liang Huang. 2013 · 2013
Earlier work this paper cites.
Event extraction via dynamic multi-pooling convolutional neural networks
Yubo Chen, Liheng Xu, Kang Liu, Daojian Zeng, and Jun Zhao. 2015 · 2015
Earlier work this paper cites.
Joint event extraction via recurrent neural networks
Thien Huu Nguyen, Kyunghyun Cho, and Ralph Grishman. 2016 · 2016
Earlier work this paper cites.
Zero-shot transfer learning for event extraction
Lifu Huang, Heng Ji, Kyunghyun Cho, Ido Dagan, Sebastian Riedel, and Clare Voss. 2018 · 2018
Earlier work this paper cites.
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
Earlier work this paper cites.
DCFEE: A document-level Chinese financial event extraction system based on automatically labeled training data
Hang Yang, Yubo Chen, Kang Liu, Yang Xiao, and Jun Zhao. 2018 · 2018
Earlier work this paper cites.
Entity, relation, and event extraction with contextualized span representations
David Wadden, Ulme Wennberg, Yi Luan, and Hannaneh Hajishirzi. 2019 · 2019
Earlier work this paper cites.
Doc2EDAG: An end-to-end document-level framework for Chinese financial event extraction
Shun Zheng, Wei Cao, Wei Xu, and Jiang Bian. 2019 · 2019
Earlier work this paper cites.
End-to-end object detection with transformers
N. Carion, F. Massa, G. Synnaeve, N. Usunier, A. Kirillov, and S. Zagoruyko. 2020 · 2020
Cited alongside, same era.
Event extraction by answering (almost) natural questions
Xinya Du and Claire Cardie. 2020 · 2020
Cited alongside, same era.
Multi-sentence argument linking
Seth Ebner, Patrick Xia, Ryan Culkin, Kyle Rawlins, and Benjamin Van Durme. 2020 · 2020
Cited alongside, same era.
BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
Event extraction as multi-turn question answering
Fayuan Li, Weihua Peng, Yuguang Chen, Quan Wang, Lu Pan, Yajuan Lyu, and Yong Zhu. 2020 · 2020
Cited alongside, same era.
A joint neural model for information extraction with global features
Document-level event argument extraction by conditional generation
Sha Li, Heng Ji, and Jiawei Han. 2021 · 2021
Later among the works it cites.
Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang. 2021 · 2021
Later among the works it cites.
Machine reading comprehension as data augmentation: A case study on implicit event argument extraction
Jian Liu, Yufeng Chen, and Jinan Xu. 2021a · 2021
Later among the works it cites.
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
Later among the works it cites.
Structured prediction as translation between augmented natural languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, Rishita Anubhai, Cícero Nogueira dos Santos, Bing Xiang, and Stefano Soatto. 2021 · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Ying Lin, Heng Ji, Fei Huang, and Lingfei Wu. 2020 · 2020
Cited alongside, same era.
Event extraction as machine reading comprehension
Jian Liu, Yubo Chen, Kang Liu, Wei Bi, and Xiaojiang Liu. 2020 · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
Cited alongside, same era.
Template-based named entity recognition using BART
Leyang Cui, Yu Wu, Jian Liu, Sen Yang, and Yue Zhang. 2021 · 2021
Cited alongside, same era.
Document-level event extraction with efficient end-to-end learning of cross-event dependencies
Kung-Hsiang Huang and Nanyun Peng. 2021 · 2021
Cited alongside, same era.
Exploring sentence community for document-level event extraction
Yusheng Huang and Weijia Jia. 2021 · 2021
Cited alongside, same era.
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2021b
Cited in the paper.
Learning how to ask: Querying LMs with mixtures of soft prompts
Guanghui Qin and Jason Eisner. 2021 · 2021
Later among the works it cites.
Exploiting cloze-questions for few-shot text classification and natural language inference
Timo Schick and Hinrich Schütze. 2021 · 2021
Later among the works it cites.
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. 2021 · 2021
Later among the works it cites.
Trigger is not sufficient: Exploiting frame-aware knowledge for implicit event argument extraction
Kaiwen Wei, Xian Sun, Zequn Zhang, Jingyuan Zhang, Guo Zhi, and Li Jin. 2021 · 2021
Later among the works it cites.
Document-level event extraction via heterogeneous graph-based interaction model with a tracker
Runxin Xu, Tianyu Liu, Lei Li, and Baobao Chang. 2021 · 2021
Later among the works it cites.
Document-level event extraction via parallel prediction networks
Hang Yang, Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, and Taifeng Wang. 2021 · 2021
Later among the works it cites.