Fetching the paper…
Reading the bibliography…
Recent years have seen the paradigm shift of Named Entity Recognition (NER) systems from sequence labeling to span prediction.
Critical values and probability levels for the wilcoxon rank sum test and the wilcoxon signed rank test
Frank Wilcoxon, SK Katti, and Roberta A Wilcox. 1970 · 1970
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Stacked generalizations: When does it work?
Kai Ming Ting and Ian H. Witten. 1997 · 1997
Earlier work this paper cites.
Support vector machines
Marti A. Hearst, Susan T Dumais, Edgar Osuna, John Platt, and Bernhard Scholkopf. 1998 · 1998
Earlier work this paper cites.
Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors)
Jerome Friedman, Trevor Hastie, Robert Tibshirani, et al. 2000 · 2000
Earlier work this paper cites.
Random forests
Leo Breiman. 2001 · 2001
Earlier work this paper cites.
Introduction to the conll-2002 shared task: Language-independent named entity recognition
Erik F. Tjong Kim Sang. 2002 · 2002
Earlier work this paper cites.
Named entity recognition through classifier combination
Radu Florian, Abe Ittycheriah, Hongyan Jing, and Tong Zhang. 2003 · 2003
Earlier work this paper cites.
Introduction to the conll-2003 shared task: Language-independent named entity recognition
Erik F Sang and Fien De Meulder. 2003 · 2003
Earlier work this paper cites.
A stacked, voted, stacked model for named entity recognition
Dekai Wu, Grace Ngai, and Marine Carpuat. 2003 · 2003
Earlier work this paper cites.
Instance-based learning of span representations: A case study through named entity recognition
Hiroki Ouchi, Jun Suzuki, Sosuke Kobayashi, Sho Yokoi, Tatsuki Kuribayashi, Ryuto Konno, and Kentaro Inui. 2020 · 2004
Earlier work this paper cites.
Discriminative reranking for natural language parsing
Michael Collins and Terry Koo. 2005 · 2005
Earlier work this paper cites.
Forest reranking: Discriminative parsing with non-local features
Liang Huang. 2008 · 2008
Earlier work this paper cites.
Natural language processing (almost) from scratch
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa. 2011 · 2011
Earlier work this paper cites.
Generalized minimum bayes risk system combination
Kevin Duh, Katsuhito Sudoh, Xianchao Wu, Hajime Tsukada, and Masaaki Nagata. 2011 · 2011
Earlier work this paper cites.
Weighted vote-based classifier ensemble for named entity recognition: A genetic algorithm-based approach
Asif Ekbal and Sriparna Saha. 2011 · 2011
Earlier work this paper cites.
Minimum Bayes-risk system combination
Jesús González-Rubio, Alfons Juan, and Francisco Casacuberta. 2011 · 2011
Earlier work this paper cites.
Machine translation system combination by confusion forest
Taro Watanabe and Eiichiro Sumita. 2011 · 2011
Earlier work this paper cites.
Combining multiple classifiers using vote based classifier ensemble technique for named entity recognition
Sriparna Saha and Asif Ekbal. 2013 · 2013
Earlier work this paper cites.
Ontonotes release 5.0 ldc2013t19
Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, et al. 2013 · 2013
Earlier work this paper cites.
A joint model for entity analysis: Coreference, typing, and linking
Greg Durrett and Dan Klein. 2014 · 2014
Cited alongside, same era.
Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
Cited alongside, same era.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Cited alongside, same era.
Ensemble learning for named entity recognition
René Speck and Axel-Cyrille Ngonga Ngomo. 2014 · 2014
Cited alongside, same era.
A weighted voting classifier based on differential evolution
Yong Zhang, Hongrui Zhang, Jing Cai, and Binbin Yang. 2014 · 2014
Cited alongside, same era.
Named entity recognition with bidirectional lstm-cnns
Jason PC Chiu and Eric Nichols. 2015 · 2015
Pooled contextualized embeddings for named entity recognition
Alan Akbik, Tanja Bergmann, and Roland Vollgraf. 2019 · 2019
Later among the works it cites.
Grn: Gated relation network to enhance convolutional neural network for named entity recognition
Hui Chen, Zijia Lin, Guiguang Ding, Jianguang Lou, Yusen Zhang, and Borje Karlsson. 2019 · 2019
Later among the works it cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Later among the works it cites.
Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019 · 2019
Later among the works it cites.
Multi-grained named entity recognition
Congying Xia, Chenwei Zhang, Tao Yang, Yaliang Li, Nan Du, Xian Wu, Wei Fan, Fenglong Ma, and S Yu Philip. 2019 · 2019
Later among the works it cites.
Utility is in the eye of the user: A critique of NLP leaderboards
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Bidirectional lstm-crf models for sequence tagging
Zhiheng Huang, Wei Xu, and Kai Yu. 2015 · 2015
Cited alongside, same era.
Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin. 2016 · 2016
Cited alongside, same era.
Neural architectures for named entity recognition
Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer. 2016 · 2016
Cited alongside, same era.
End-to-end sequence labeling via bi-directional lstm-cnns-crf
Xuezhe Ma and Eduard Hovy. 2016 · 2016
Cited alongside, same era.
Discriminative reranking for grammatical error correction with statistical machine translation
Tomoya Mizumoto and Yuji Matsumoto. 2016 · 2016
Cited alongside, same era.
Results of the wnut16 named entity recognition shared task
Benjamin Strauss, Bethany Toma, Alan Ritter, Marie-Catherine De Marneffe, and Wei Xu. 2016 · 2016
Cited alongside, same era.
Kawin Ethayarajh and Dan Jurafsky. 2020 · 2020
Later among the works it cites.
Interpretable multi-dataset evaluation for named entity recognition
Jinlan Fu, Pengfei Liu, and Graham Neubig. 2020a · 2020
Later among the works it cites.
RethinkCWS: Is Chinese word segmentation a solved task?
Jinlan Fu, Pengfei Liu, Qi Zhang, and Xuanjing Huang. 2020c · 2020
Later among the works it cites.
Modeling voting for system combination in machine translation
Xuancheng Huang, Jiacheng Zhang, Zhixing Tan, Derek F. Wong, Huanbo Luan, Jingfang Xu, Maosong Sun, and Yang Liu. 2020 · 2020
Later among the works it cites.
Generalizing natural language analysis through span-relation representations
Zhengbao Jiang, Wei Xu, Jun Araki, and Graham Neubig. 2020 · 2020
Later among the works it cites.
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
Later among the works it cites.
A unified MRC framework for named entity recognition
Xiaoya Li, Jingrong Feng, Yuxian Meng, Qinghong Han, Fei Wu, and Jiwei Li. 2020 · 2020
Later among the works it cites.
Triggerner: Learning with entity triggers as explanations for named entity recognition
Bill Yuchen Lin, Dong-Ho Lee, Ming Shen, Ryan Moreno, Xiao Huang, Prashant Shiralkar, and Xiang Ren. 2020 · 2020
Later among the works it cites.
Hierarchical contextualized representation for named entity recognition
Ying Luo, Fengshun Xiao, and Hai Zhao. 2020 · 2020
Later among the works it cites.
Coarse-to-fine pre-training for named entity recognition
Xue Mengge, Bowen Yu, Zhenyu Zhang, Tingwen Liu, Yue Zhang, and Bin Wang. 2020 · 2020
Later among the works it cites.
LUKE: Deep contextualized entity representations with entity-aware self-attention
Ikuya Yamada, Akari Asai, Hiroyuki Shindo, Hideaki Takeda, and Yuji Matsumoto. 2020 · 2020
Later among the works it cites.
Named entity recognition as dependency parsing
Juntao Yu, Bernd Bohnet, and Massimo Poesio. 2020 · 2020
Later among the works it cites.
Larger-context tagging: When and why does it work?
Jinlan Fu, Liangjing Feng, Qi Zhang, Xuanjing Huang, and Pengfei Liu. 2021 · 2021
Closest in time.
Explainaboard: An explainable leaderboard for nlp
Pengfei Liu, Jinlan Fu, Yang Xiao, Weizhe Yuan, Shuaicheng Chang, Junqi Dai, Yixin Liu, Zihuiwen Ye, and Graham Neubig. 2021 · 2021
Closest in time.