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Event argument extraction has long been studied as a sequential prediction problem with extractive-based methods, tackling each argument in isolation.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Minimum hellinger distance estimates for parametric models
Rudolf Beran. 1977 · 1977
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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
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Extracting complex biological events with rich graph-based feature sets
Jari Björne, Juho Heimonen, Filip Ginter, Antti Airola, Tapio Pahikkala, and Tapio Salakoski. 2009 · 2009
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Modeling textual cohesion for event extraction
Ruihong Huang and Ellen Riloff. 2012 · 2012
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Joint event extraction via structured prediction with global features
Qi Li, Heng Ji, and Liang Huang. 2013 · 2013
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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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Joint event extraction via recurrent neural networks
Thien Huu Nguyen, Kyunghyun Cho, and Ralph Grishman. 2016 · 2016
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Joint extraction of events and entities within a document context
Bishan Yang and Tom M. Mitchell. 2016 · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Entity, relation, and event extraction with contextualized span representations
David Wadden, Ulme Wennberg, Yi Luan, and Hannaneh Hajishirzi. 2019 · 2019
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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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. 2020 · 2020
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Template filling with generative transformers
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Document-level entity-based extraction as template generation
Kung-Hsiang Huang, Sam Tang, and Nanyun Peng. 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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Event extraction by answering (almost) natural questions
Xinya Du and Claire Cardie. 2020b · 2020
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Realm: retrieval-augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020 · 2020
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Speech and language processing
Daniel Jurafsky and James H Martin. 2018 · 2020
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Document-level event role filler extraction using multi-granularity contextualized encoding
Xinya Du and Claire Cardie. 2020a
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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. 2020a
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al. 2020b
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Tianhao Wang, Si Chen, and Ruoxi Jia. 2021 · 2021
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Dynamic global memory for document-level argument extraction
Xinya Du, Sha Li, and Heng Ji. 2022 · 2022
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Multilingual generative language models for zero-shot cross-lingual event argument extraction
Kuan-Hao Huang, I-Hung Hsu, Prem Natarajan, Kai-Wei Chang, and Nanyun Peng. 2022 · 2022
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What makes good in-context examples for gpt-3?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, William B Dolan, Lawrence Carin, and Weizhu Chen. 2022 · 2022
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