DocBERT: BERT for Document Classification

Distilling task-specific knowledge from BERT into simple neural networks

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XLNet: generalized autoregressive pretraining for language understanding

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Do deep nets really need to be deep?

Jimmy Ba and Rich Caruana. 2014 · 2014

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Convolutional neural networks for sentence classification

Yoon Kim. 2014 · 2014

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GloVe: global vectors for word representation

Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014

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Event extraction via dynamic multi-pooling convolutional neural networks

Yubo Chen, Liheng Xu, Kang Liu, Daojian Zeng, and Jun Zhao. 2015 · 2015

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Distilling the knowledge in a neural network

Geoffrey E. Hinton, Oriol Vinyals, and Jeffrey Dean. 2015 · 2015

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Effective use of word order for text categorization with convolutional neural networks

Rie Johnson and Tong Zhang. 2015 · 2015

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Document modeling with gated recurrent neural network for sentiment classification

Duyu Tang, Bing Qin, and Ting Liu. 2015 · 2015

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Hierarchical attention networks for document classification

Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 · 2016

Learning sparse neural networks through l 0 l_{0} regularization

Christos Louizos, Max Welling, and Diederik P. Kingma. 2018 · 2018

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Deep contextualized word representations

Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018

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Improving language understanding by generative pre-training

Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018

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SGM: sequence generation model for multi-label classification

Pengcheng Yang, Xu Sun, Wei Li, Shuming Ma, Wei Wu, and Houfeng Wang. 2018 · 2018

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Rethinking complex neural network architectures for document classification

Ashutosh Adhikari, Achyudh Ram, Raphael Tang, and Jimmy Lin. 2019 · 2019

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BERT: pre-training of deep bidirectional transformers for language understanding