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While coreference resolution typically involves various linguistic challenges, recent models are based on a single pairwise scorer for all types of pairs.
A model-theoretic coreference scoring scheme
Marc Vilain, John Burger, John Aberdeen, Dennis Connolly, and Lynette Hirschman. 1995 · 1995
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Entity-based cross-document coreferencing using the vector space model
Amit Bagga and Breck Baldwin. 1998 · 1998
Earlier work this paper cites.
A machine learning approach to coreference resolution of noun phrases
Wee Meng Soon, Hwee Tou Ng, and Daniel Chung Yong Lim. 2001 · 2001
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Longformer: The long-document transformer
Iz Beltagy, Matthew E. Peters, and Arman Cohan. 2020 · 2004
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A high-performance coreference resolution system using a constraint-based multi-agent strategy
GuoDong Zhou and Jian Su. 2004 · 2004
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On coreference resolution performance metrics
Xiaoqiang Luo. 2005 · 2005
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Understanding the value of features for coreference resolution
Eric Bengtson and Dan Roth. 2008 · 2008
Earlier work this paper cites.
Specialized models and ranking for coreference resolution
Pascal Denis and Jason Baldridge. 2008 · 2008
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Simple coreference resolution with rich syntactic and semantic features
Aria Haghighi and Dan Klein. 2009 · 2009
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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.
Improving pairwise coreference models through feature space hierarchy learning
Emmanuel Lassalle and Pascal Denis. 2013 · 2013
Earlier work this paper cites.
Deterministic coreference resolution based on entity-centric, precision-ranked rules
Heeyoung Lee, Angel Chang, Yves Peirsman, Nathanael Chambers, Mihai Surdeanu, and Dan Jurafsky. 2013 · 2013
Earlier work this paper cites.
Entity-centric coreference resolution with model stacking
Kevin Clark and Christopher D. Manning. 2015 · 2015
Earlier work this paper cites.
Improving coreference resolution by learning entity-level distributed representations
Kevin Clark and Christopher D. Manning. 2016 · 2016
Cited alongside, same era.
WikiCoref: An English coreference-annotated corpus of Wikipedia articles
Abbas Ghaddar and Phillippe Langlais. 2016 · 2016
Cited alongside, same era.
Which coreference evaluation metric do you trust? a proposal for a link-based entity aware metric
Nafise Sadat Moosavi and Michael Strube. 2016 · 2016
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.
Higher-order coreference resolution with coarse-to-fine inference
Kenton Lee, Luheng He, and Luke Zettlemoyer. 2018 · 2018
Cited alongside, same era.
Gender bias in coreference resolution
Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme. 2018 · 2018
Conundrums in entity coreference resolution: Making sense of the state of the art
Jing Lu and Vincent Ng. 2020 · 2020
Later among the works it cites.
Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks
Shubham Toshniwal, Sam Wiseman, Allyson Ettinger, Karen Livescu, and Kevin Gimpel. 2020 · 2020
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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
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Incremental neural coreference resolution in constant memory
Patrick Xia, João Sedoc, and Benjamin Van Durme. 2020 · 2020
Later among the works it cites.
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Cited alongside, same era.
Mind the GAP: A balanced corpus of gendered ambiguous pronouns
Kellie Webster, Marta Recasens, Vera Axelrod, and Jason Baldridge. 2018 · 2018
Cited alongside, same era.
Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2018 · 2018
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.
Coreference resolution with entity equalization
Ben Kantor and Amir Globerson. 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.
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
Cited alongside, same era.
Revealing the myth of higher-order inference in coreference resolution
Liyan Xu and Jinho D. Choi. 2020 · 2020
Later among the works it cites.
Word-level coreference resolution
Vladimir Dobrovolskii. 2021 · 2021
Later among the works it cites.
Coreference resolution without span representations
Yuval Kirstain, Ori Ram, and Omer Levy. 2021 · 2021
Later among the works it cites.
Collecting a large-scale gender bias dataset for coreference resolution and machine translation
Shahar Levy, Koren Lazar, and Gabriel Stanovsky. 2021 · 2021
Later among the works it cites.
Scaling within document coreference to long texts
Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, Manzil Zaheer, Mrinmaya Sachan, and Andrew McCallum. 2021 · 2021
Later among the works it cites.
F-coref: Fast, accurate and easy to use coreference resolution
Shon Otmazgin, Arie Cattan, and Yoav Goldberg. 2022 · 2022
Closest in time.
deep-significance-easy and meaningful statistical significance testing in the age of neural networks
Dennis Ulmer, Christian Hardmeier, and Jes Frellsen. 2022 · 2022
Closest in time.