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Worth-reading papers and related resources on text classification. 文本分类领域值得一读的论文与相关资源集合

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TCPapers

Worth-reading papers and related resources on text classification.

Suggestions about fixing errors or adding papers, repositories and other resources are welcomed!

文本分类领域值得一读的论文与相关资源集合。

欢迎修正错误以及新增论文、代码仓库与其他资源等建议!

Papers

  • Convolutional Neural Networks for Sentence Classification. Yoon Kim. (EMNLP 2014) [paper] - TextCNN
  • Recurrent Neural Network for Text Classification with Multi-Task Learning. Pengfei Liu, Xipeng Qiu, Xuanjing Huang. (IJCAI 2016) [paper] - TextRNN
  • Recurrent Convolutional Neural Networks for Text Classification. Siwei Lai, Liheng Xu, Kang Liu, Jun Zhao. (AAAI 2015) [paper] - TextRCNN
  • Bag of Tricks for Efficient Text Classification. Armand Joulin, Edouard Grave, Piotr Bojanowski, Tomas Mikolov. (EACL 2016) [paper] - FastText
  • Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification. Peng Zhou, Wei Shi, Jun Tian, Zhenyu Qi, Bingchen Li, Hongwei Hao, Bo Xu. (ACL 2016) [paper] - Attn-BiLSTM
  • Hierarchical Attention Networks for Document Classification. Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, Eduard Hovy. (NAACL 2016) [paper] - HAN
  • Enhancing Local Feature Extraction with Global Representation for Neural Text Classification. Guocheng Niu, Hengru Xu, Bolei He, Xinyan Xiao, Hua Wu, Sheng Gao. (EMNLP 2019) [paper] [code] - GELE
  • PRADO: Projection Attention Networks for Document Classification On-Device. Prabhu Kaliamoorthi, Sujith Ravi, Zornitsa Kozareva. (EMNLP 2019) [paper][code][blog]
  • How to Fine-Tune BERT for Text Classification?. Chi Sun, Xipeng Qiu, Yige Xu, Xuanjing Huang. (CCL 2019) [paper][code]
  • Human Attention Maps for Text Classification: Do Humans and Neural Networks Focus on the Same Words?. Cansu Sen, Thomas Hartvigsen, Biao Yin, Xiangnan Kong, Elke Rundensteiner. (ACL 2020) [paper] - YELP-HAT
  • Description Based Text Classification with Reinforcement Learning. Duo Chai, Wei Wu, Qinghong Han, Fei Wu, Jiwei Li. (ICML 2020) [paper]

Label Embedding

  • Joint Embedding of Words and Labels for Text Classification. Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin. (ACL 2018) [paper][code] - LEAM
  • Multi-Task Label Embedding for Text Classification. Honglun Zhang, Liqiang Xiao, Wenqing Chen, Yongkun Wang, Yaohui Jin. (EMNLP 2018) [paper] - MTLE
  • Explicit Interaction Model towards Text Classification. Cunxiao Du, Zhaozheng Chin, Fuli Feng, Lei Zhu, Tian Gan, Liqiang Nie. (AAAI 2019) [paper][code] - EXAM
  • GILE: A Generalized Input-Label Embedding for Text Classification. Nikolaos Pappas, James Henderson (TACL Volumn 7 2019) [paper][code]

Weakly-supervised & Semi-supervised Learning

  • MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification. Jiaao Chen, Zichao Yang, Diyi Yang. (ACL 2020) [paper][code]
  • Text Classification Using Label Names Only: A Language Model Self-Training Approach. Yu Meng, Yunyi Zhang, Jiaxin Huang, Chenyan Xiong, Heng Ji, Chao Zhang, Jiawei Han. (EMNLP 2020) [paper][code] - LOTClass
  • Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference. Timo Schick, Hinrich Schütze. (EACL 2021) [paper][code]
  • It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners. Timo Schick, Hinrich Schütze. (CoRR 2020) [paper][code]
  • Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification. Timo Schick, Helmut Schmid, Hinrich Schütze. (COLING 2020) [paper][code]
  • Few-Shot Text Classification with Triplet Networks, Data Augmentation, and Curriculum Learning. Jason Wei, Chengyu Huang, Soroush Vosoughi, Yu Cheng, Shiqi Xu. (NAACL 2021) [paper]

Survey & Tutorial

  • Deep Learning Based Text Classification: A Comprehensive Review. Shervin Minaee, Nal Kalchbrenner, Erik Cambria, Narjes Nikzad, Meysam Chenaghlu, Jianfeng Gao. (CoRR 2020) [paper]

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