Fetching the paper…
Reading the bibliography…
Biomedical named entity recognition (BNER) serves as the foundation for numerous biomedical text mining tasks.
Genia corpus—a semantically annotated corpus for bio-textmining
J-D Kim, Tomoko Ohta, Yuka Tateisi, and Jun’ichi Tsujii. 2003 · 2003
Earlier work this paper cites.
Introduction to the bio-entity recognition task at jnlpba
Nigel Collier and Jin-Dong Kim. 2004 · 2004
Earlier work this paper cites.
Overview of biocreative ii gene mention recognition
Larry Smith, Lorraine K Tanabe, Cheng-Ju Kuo, I Chung, Chun-Nan Hsu, Yu-Shi Lin, Roman Klinger, Christoph M Friedrich, Kuzman Ganchev, Manabu Torii, et al. 2008 · 2008
Earlier work this paper cites.
Training conditional random fields using incomplete annotations
Yuta Tsuboi, Hisashi Kashima, Shinsuke Mori, Hiroki Oda, and Yuji Matsumoto. 2008 · 2008
Earlier work this paper cites.
Linnaeus: a species name identification system for biomedical literature
Martin Gerner, Goran Nenadic, and Casey M Bergman. 2010 · 2010
Earlier work this paper cites.
The species and organisms resources for fast and accurate identification of taxonomic names in text
Evangelos Pafilis, Sune P Frankild, Lucia Fanini, Sarah Faulwetter, Christina Pavloudi, Aikaterini Vasileiadou, Christos Arvanitidis, and Lars Juhl Jensen. 2013 · 2013
Earlier work this paper cites.
Ncbi disease corpus: a resource for disease name recognition and concept normalization
Rezarta Islamaj Doğan, Robert Leaman, and Zhiyong Lu. 2014 · 2014
Earlier work this paper cites.
The chemdner corpus of chemicals and drugs and its annotation principles
Martin Krallinger, Obdulia Rabal, Florian Leitner, Miguel Vazquez, David Salgado, Zhiyong Lu, Robert Leaman, Yanan Lu, Donghong Ji, Daniel M Lowe, et al. 2015 · 2015
Earlier work this paper cites.
Named entity recognition with bidirectional lstm-cnns
Jason PC Chiu and Eric Nichols. 2016 · 2016
Earlier work this paper cites.
Biocreative v cdr task corpus: a resource for chemical disease relation extraction
Jiao Li, Yueping Sun, Robin J Johnson, Daniela Sciaky, Chih-Hsuan Wei, Robert Leaman, Allan Peter Davis, Carolyn J Mattingly, Thomas C Wiegers, and Zhiyong Lu. 2016 · 2016
Earlier work this paper cites.
End-to-end sequence labeling via bi-directional lstm-cnns-crf
Xuezhe Ma and Eduard Hovy. 2016 · 2016
Cited alongside, same era.
Deep learning with word embeddings improves biomedical named entity recognition
Maryam Habibi, Leon Weber, Mariana Neves, David Luis Wiegandt, and Ulf Leser. 2017 · 2017
Cited alongside, same era.
A local detection approach for named entity recognition and mention detection
Mingbin Xu, Hui Jiang, and Sedtawut Watcharawittayakul. 2017 · 2017
Cited alongside, same era.
Transfer learning for biomedical named entity recognition with neural networks
John M Giorgi and Gary D Bader. 2018 · 2018
Cited alongside, same era.
Marginal likelihood training of bilstm-crf for biomedical named entity recognition from disjoint label sets
Nathan Greenberg, Trapit Bansal, Patrick Verga, and Andrew McCallum. 2018 · 2018
Cited alongside, same era.
Deep exhaustive model for nested named entity recognition
Cross-type biomedical named entity recognition with deep multi-task learning
Xuan Wang, Yu Zhang, Xiang Ren, Yuhao Zhang, Marinka Zitnik, Jingbo Shang, Curtis Langlotz, and Jiawei Han. 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.
Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 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.
Bond: Bert-assisted open-domain named entity recognition with distant supervision
Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, and Chao Zhang. 2020 · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Mohammad Golam Sohrab and Makoto Miwa. 2018 · 2018
Cited alongside, same era.
Low-resource name tagging learned with weakly labeled data
Yixin Cao, Zikun Hu, Tat-Seng Chua, Zhiyuan Liu, and Heng Ji. 2019 · 2019
Cited alongside, same era.
Learning a unified named entity tagger from multiple partially annotated corpora for efficient adaptation
Xiao Huang, Li Dong, Elizabeth Boschee, and Nanyun Peng. 2019 · 2019
Cited alongside, same era.
Better modeling of incomplete annotations for named entity recognition
Zhanming Jie, Pengjun Xie, Wei Lu, Ruixue Ding, and Linlin Li. 2019 · 2019
Cited alongside, same era.
Named entity recognition with partially annotated training data
Stephen Mayhew, Snigdha Chaturvedi, Chen-Tse Tsai, and Dan Roth. 2019 · 2019
Cited alongside, same era.
Self-alignment pretraining for biomedical entity representations
Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, Marco Basaldella, and Nigel Collier. 2020a
Cited in the paper.
Hamner: Headword amplified multi-span distantly supervised method for domain specific named entity recognition
Shifeng Liu, Yifang Sun, Bing Li, Wei Wang, and Xiang Zhao. 2020b
Cited in the paper.
Nested named entity recognition via second-best sequence learning and decoding
Takashi Shibuya and Eduard Hovy. 2020 · 2020
Later among the works it cites.
Tebner: Domain specific named entity recognition with type expanded boundary-aware network
Zheng Fang, Yanan Cao, Tai Li, Ruipeng Jia, Fang Fang, Yanmin Shang, and Yuhai Lu. 2021 · 2021
Later among the works it cites.
Spanner: Named entity re-/recognition as span prediction
Jinlan Fu, Xuan-Jing Huang, and Pengfei Liu. 2021 · 2021
Later among the works it cites.
Optimizing bi-encoder for named entity recognition via contrastive learning
Sheng Zhang, Hao Cheng, Jianfeng Gao, and Hoifung Poon. 2022 · 2022
Later among the works it cites.