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Coreference resolution has been mostly investigated within a single document scope, showing impressive progress in recent years based on end-to-end models.
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
Earlier work this paper cites.
Unsupervised event coreference resolution with rich linguistic features
Cosmin Bejan and Sanda Harabagiu. 2010 · 2010
Earlier work this paper cites.
Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio. 2010 · 2010
Earlier work this paper cites.
Cross-document event coreference resolution beyond corpus-tailored systems
Michael Bugert, N. Reimers, and Iryna Gurevych. 2020 · 2011
Earlier work this paper cites.
Joint entity and event coreference resolution across documents
Heeyoung Lee, Marta Recasens, Angel Chang, Mihai Surdeanu, and Dan Jurafsky. 2012 · 2012
Earlier work this paper cites.
CoNLL-2012 shared task: Modeling multilingual unrestricted coreference in OntoNotes
Sameer Pradhan, Alessandro Moschitti, Nianwen Xue, Olga Uryupina, and Yuchen Zhang. 2012 · 2012
Earlier work this paper cites.
Using a sledgehammer to crack a nut? lexical diversity and event coreference resolution
Agata Cybulska and Piek Vossen. 2014 · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Translating granularity of event slots into features for event coreference resolution
Agata Cybulska and Piek Vossen. 2015 · 2015
Earlier work this paper cites.
A hierarchical distance-dependent Bayesian model for event coreference resolution
Bishan Yang, Claire Cardie, and Peter Frazier. 2015 · 2015
Cited alongside, same era.
Event coreference resolution by iteratively unfolding inter-dependencies among events
Prafulla Kumar Choubey and Ruihong Huang. 2017 · 2017
Cited alongside, same era.
End-to-end neural coreference resolution
Kenton Lee, Luheng He, Mike Lewis, and Luke Zettlemoyer. 2017 · 2017
Cited alongside, same era.
Acquiring predicate paraphrases from news tweets
Vered Shwartz, Gabriel Stanovsky, and Ido Dagan. 2017 · 2017
Cited alongside, same era.
Resolving event coreference with supervised representation learning and clustering-oriented regularization
Kian Kenyon-Dean, Jackie Chi Kit Cheung, and Doina Precup. 2018 · 2018
Cited alongside, same era.
Revisiting joint modeling of cross-document entity and event coreference resolution
SpanBERT: Improving pre-training by representing and predicting spans
Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. Weld, Luke Zettlemoyer, and Omer Levy. 2020 · 2020
Later among the works it cites.
Paraphrasing vs coreferring: Two sides of the same coin
Yehudit Meged, Avi Caciularu, Vered Shwartz, and Ido Dagan. 2020 · 2020
Later among the works it cites.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Later among the works it cites.
CorefQA: Coreference resolution as query-based span prediction
Wei Wu, Fei Wang, Arianna Yuan, Fei Wu, and Jiwei Li. 2020 · 2020
Later among the works it cites.
Event coreference resolution with their paraphrases and argument-aware embeddings
Yutao Zeng, Xiaolong Jin, Saiping Guan, Jiafeng Guo, and Xueqi Cheng. 2020 · 2020
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Shany Barhom, Vered Shwartz, Alon Eirew, Michael Bugert, Nils Reimers, and Ido Dagan. 2019 · 2019
Cited alongside, same era.
BERT for coreference resolution: Baselines and analysis
Mandar Joshi, Omer Levy, Luke Zettlemoyer, and Daniel Weld. 2019 · 2019
Cited alongside, same era.
Scalable Hierarchical Clustering with Tree Grafting
Nicholas Monath, A. Kobren, A. Krishnamurthy, Michael R. Glass, and A. McCallum. 2019 · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
Cited alongside, same era.
Later among the works it cites.
Cross-document language modeling
Avi Caciularu, Arman Cohan, Iz Beltagy, Matthew E. Peters, Arie Cattan, and Ido Dagan. 2021 · 2021
Closest in time.
Realistic evaluation principles for cross-document coreference resolution
Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, and Ido Dagan. 2021 · 2021
Closest in time.
Scalable Bottom-up Hierarchical Clustering
Nicholas Monath, Kumar Avinava Dubey, Guru Guruganesh, M. Zaheer, Amr Ahmed, A. McCallum, Gokhan Mergen, Marc Najork, Mert Terzihan, B. Tjanaka, Yuan Wang, and Yuchen Wu. 2021 · 2021
Closest in time.