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Recently, large-scale datasets have vastly facilitated the development in nearly all domains of Natural Language Processing.
ERNIE: enhanced representation through knowledge integration
Yu Sun, Shuohuan Wang, Yu-Kun Li, Shikun Feng, Xuyi Chen, Han Zhang, Xin Tian, Danxiang Zhu, Hao Tian, and Hua Wu. 2019 · 1904
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2019 · 1910
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The TREC-8 question answering track evaluation
Ellen M. Voorhees and Dawn M. Tice. 1999 · 1999
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Bert-of-theseus: Compressing BERT by progressive module replacing
Canwen Xu, Wangchunshu Zhou, Tao Ge, Furu Wei, and Ming Zhou. 2020 · 2002
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Automatic evaluation of summaries using n-gram co-occurrence statistics
Chin-Yew Lin and Eduard H. Hovy. 2003 · 2003
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Lexrank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R. Radev. 2004 · 2004
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Textrank: Bringing order into text
Rada Mihalcea and Paul Tarau. 2004 · 2004
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Fei-Fei Li. 2009 · 2009
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Speech and language processing: an introduction to natural language processing, computational linguistics, and speech recognition, 2nd Edition
Dan Jurafsky and James H. Martin. 2009 · 2009
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Annotated gigaword
Courtney Napoles, Matthew R. Gormley, and Benjamin Van Durme. 2012 · 2012
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A convolutional neural network for modelling sentences
Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. 2014 · 2014
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Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014 · 2014
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
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LCSTS: A large scale chinese short text summarization dataset
Baotian Hu, Qingcai Chen, and Fangze Zhu. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Recurrent convolutional neural networks for text classification
Siwei Lai, Liheng Xu, Kang Liu, and Jun Zhao. 2015 · 2015
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Representation learning using multi-task deep neural networks for semantic classification and information retrieval
Xiaodong Liu, Jianfeng Gao, Xiaodong He, Li Deng, Kevin Duh, and Ye-Yi Wang. 2015 · 2015
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Effective approaches to attention-based neural machine translation
Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Jake Zhao, and Yann LeCun. 2015 · 2015
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Consensus attention-based neural networks for chinese reading comprehension
Yiming Cui, Ting Liu, Zhipeng Chen, Shijin Wang, and Guoping Hu. 2016 · 2016
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The goldilocks principle: Reading children’s books with explicit memory representations
Felix Hill, Antoine Bordes, Sumit Chopra, and Jason Weston. 2016 · 2016
Cited alongside, same era.
Multi-task sequence to sequence learning
Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, Oriol Vinyals, and Lukasz Kaiser. 2016 · 2016
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MS MARCO: A human generated machine reading comprehension dataset
Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng. 2016 · 2016
Cited alongside, same era.
Squad: 100, 000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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THUCTC: An efficient chinese text classifier
Maosong Sun, Jingyang Li, Zhipeng Guo, Yu Zhao, Yabin Zheng, Xiance Si, and Zhiyuan Liu. 2016 · 2016
Cited alongside, same era.
Query and output: Generating words by querying distributed word representations for paraphrase generation
Shuming Ma, Xu Sun, Wei Li, Sujian Li, Wenjie Li, and Xuancheng Ren. 2018 · 2018
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The natural language decathlon: Multitask learning as question answering
Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, and Richard Socher. 2018 · 2018
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
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Directional skip-gram: Explicitly distinguishing left and right context for word embeddings
Yan Song, Shuming Shi, Jing Li, and Haisong Zhang. 2018 · 2018
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Super characters: A conversion from sentiment classification to image classification
Baohua Sun, Lin Yang, Patrick Dong, Wenhan Zhang, Jason Dong, and Charles Young. 2018 · 2018
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Sequence-to-sequence learning as beam-search optimization
Sam Wiseman and Alexander M. Rush. 2016 · 2016
Cited alongside, same era.
Reading wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
Cited alongside, same era.
Overview of the NLPCC 2017 shared task: Open domain chinese question answering
Nan Duan and Duyu Tang. 2017 · 2017
Cited alongside, same era.
Searchqa: A new q&a dataset augmented with context from a search engine
Matthew Dunn, Levent Sagun, Mike Higgins, V. Ugur Güney, Volkan Cirik, and Kyunghyun Cho. 2017 · 2017
Cited alongside, same era.
Bag of tricks for efficient text classification
Edouard Grave, Tomas Mikolov, Armand Joulin, and Piotr Bojanowski. 2017 · 2017
Cited alongside, same era.
Deep pyramid convolutional neural networks for text categorization
Rie Johnson and Tong Zhang. 2017 · 2017
Cited alongside, same era.
Adversarial multi-task learning for text classification
Pengfei Liu, Xipeng Qiu, and Xuanjing Huang. 2017 · 2017
Cited alongside, same era.
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One-shot learning for question-answering in gaokao history challenge
Zhuosheng Zhang and Hai Zhao. 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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Unified language model pre-training for natural language understanding and generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon. 2019 · 2019
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Is word segmentation necessary for deep learning of chinese representations?
Xiaoya Li, Yuxian Meng, Xiaofei Sun, Qinghong Han, Arianna Yuan, and Jiwei Li. 2019 · 2019
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Multi-task deep neural networks for natural language understanding
Xiaodong Liu, Pengcheng He, Weizhu Chen, and Jianfeng Gao. 2019 · 2019
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Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Latent multi-task architecture learning
Sebastian Ruder, Joachim Bingel, Isabelle Augenstein, and Anders Søgaard. 2019 · 2019
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BIGPATENT: A large-scale dataset for abstractive and coherent summarization
Eva Sharma, Chen Li, and Lu Wang. 2019 · 2019
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Multi-task learning for conversational question answering over a large-scale knowledge base
Tao Shen, Xiubo Geng, Tao Qin, Daya Guo, Duyu Tang, Nan Duan, Guodong Long, and Daxin Jiang. 2019 · 2019
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Glyce: Glyph-vectors for chinese character representations
Wei Wu, Yuxian Meng, Qinghong Han, Muyu Li, Xiaoya Li, Jie Mei, Ping Nie, Xiaofei Sun, and Jiwei Li. 2019 · 2019
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Multi-task learning with sample re-weighting for machine reading comprehension
Yichong Xu, Xiaodong Liu, Yelong Shen, Jingjing Liu, and Jianfeng Gao. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. 2019 · 2019
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Selection bias explorations and debias methods for natural language sentence matching datasets
Guanhua Zhang, Bing Bai, Jian Liang, Kun Bai, Shiyu Chang, Mo Yu, Conghui Zhu, and Tiejun Zhao. 2019 · 2019
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Estimation-action-reflection: Towards deep interaction between conversational and recommender systems
Wenqiang Lei, Xiangnan He, Yisong Miao, Qingyun Wu, Richang Hong, Min-Yen Kan, and Tat-Seng Chua. 2020 · 2020
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