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Neural named entity recognition (NER) models may easily encounter the over-confidence issue, which degrades the performance and calibration.
Pre-training with whole word masking for Chinese BERT
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RoBERTa: A robustly optimized BERT pretraining approach
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Fantastic generalization measures and where to find them
Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, and Samy Bengio. 2019 · 1912
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Multilayer feedforward networks are universal approximators
Kurt Hornik, Maxwell Stinchcombe, and Halbert White. 1989 · 1989
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Flat minima
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Representing text chunks
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The third international Chinese language processing bakeoff: Word segmentation and named entity recognition
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Natural language processing (almost) from scratch
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa. 2011 · 2011
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Named entity recognition with bilingual constraints
Wanxiang Che, Mengqiu Wang, Christopher D. Manning, and Ting Liu. 2013 · 2013
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On the difficulty of training recurrent neural networks
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Towards robust linguistic analysis using OntoNotes
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Bidirectional LSTM-CRF models for sequence tagging
Zhiheng Huang, Wei Xu, and Kai Yu. 2015 · 2015
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Joint mention extraction and classification with mention hypergraphs
Wei Lu and Dan Roth. 2015 · 2015
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Named entity recognition for Chinese social media with jointly trained embeddings
Nanyun Peng and Mark Dredze. 2015 · 2015
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Named entity recognition with bidirectional LSTM-CNNs
Jason P.C. Chiu and Eric Nichols. 2016 · 2016
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Neural architectures for named entity recognition
Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer. 2016 · 2016
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End-to-end sequence labeling via bi-directional LSTM-CNNs-CRF
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger. 2017 · 2017
Learning transferable architectures for scalable image recognition
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V Le. 2018 · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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When does label smoothing help?
Rafael Müller, Simon Kornblith, and Geoffrey E Hinton. 2019 · 2019
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Neural architectures for nested NER through linearization
Jana Straková, Milan Straka, and Jan Hajic. 2019 · 2019
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CrossWeigh: Training named entity tagger from imperfect annotations
Zihan Wang, Jingbo Shang, Liyuan Liu, Lihao Lu, Jiacheng Liu, and Jiawei Han. 2019 · 2019
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Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Shijin Wang, and Guoping Hu. 2020 · 2020
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Attention is all you need
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Contextual string embeddings for sequence labeling
Alan Akbik, Duncan Blythe, and Roland Vollgraf. 2018 · 2018
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A neural layered model for nested named entity recognition
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Nested named entity recognition revisited
Arzoo Katiyar and Claire Cardie. 2018 · 2018
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Does label smoothing mitigate label noise?
Michal Lukasik, Srinadh Bhojanapalli, Aditya Menon, and Sanjiv Kumar. 2020 · 2020
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Simplify the usage of lexicon in Chinese NER
Ruotian Ma, Minlong Peng, Qi Zhang, Zhongyu Wei, and Xuanjing Huang. 2020 · 2020
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Named entity recognition as dependency parsing
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Enhancing entity boundary detection for better Chinese named entity recognition
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A span-based model for joint overlapped and discontinuous named entity recognition
Fei Li, ZhiChao Lin, Meishan Zhang, and Donghong Ji. 2021 · 2021
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Locate and label: A two-stage identifier for nested named entity recognition
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MECT: Multi-metadata embedding based cross-transformer for Chinese named entity recognition
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