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Large-scale Pretrained Language Models (PLMs) have become the new paradigm for Natural Language Processing (NLP).
Consensus attention-based neural networks for Chinese reading comprehension
Yiming Cui, Ting Liu, Zhipeng Chen, Shijin Wang, and Guoping Hu · 2016
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The LAMBADA dataset: Word prediction requiring a broad discourse context
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Dataset and neural recurrent sequence labeling model for open-domain factoid question answering
Peng Li, Wei Li, Zhengyan He, Xuguang Wang, Ying Cao, Jie Zhou, and Wei Xu · 2016
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Attention is all you need
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DuReader: A Chinese machine reading comprehension dataset from real-world applications
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Outrageously large neural networks: The sparsely-gated mixture-of-experts layer, 2017
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, and Jeff Dean · 2017
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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Mesh-TensorFlow: Deep learning for supercomputers
Noam Shazeer, Youlong Cheng, Niki Parmar, Dustin Tran, Ashish Vaswani, Penporn Koanantakool, Peter Hawkins, HyoukJoong Lee, Mingsheng Hong, Cliff Young, Ryan Sepassi, and Blake Hechtman · 2018
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Exploring hidden dimensions in accelerating convolutional neural networks
Zhihao Jia, Sina Lin, Charles R. Qi, and Alex Aiken · 2018
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Dataset for the first evaluation on Chinese machine reading comprehension
Yiming Cui, Ting Liu, Zhipeng Chen, Wentao Ma, Shijin Wang, and Guoping Hu · 2018
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DRCD: A Chinese machine reading comprehension dataset
Chih Chieh Shao, Trois Liu, Yuting Lai, Yiying Tseng, and Sam Tsai · 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
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XLNet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V. Le · 2019
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RoBERTa: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
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ERNIE: Enhanced representation through knowledge integration
Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng, Xuyi Chen, Han Zhang, Xin Tian, Danxiang Zhu, Hao Tian, and Hua Wu · 2019
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ERNIE: Enhanced language representation with informative entities
Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu · 2019
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Nezha: Neural contextualized representation for chinese language understanding, 2019
Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen, and Qun Liu · 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
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DaVinci: A scalable architecture for neural network computing
Heng Liao, Jiajin Tu, Jing Xia, and Xiping Zhou · 2019
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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 · 2020
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On layer normalization in the transformer architecture
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, and Tieyan Liu · 2020
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CLUECorpus2020: A large-scale Chinese corpus for pre-training language model
Liang Xu, Xuanwei Zhang, and Qianqian Dong · 2020
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GShard: Scaling giant models with conditional computation and automatic sharding
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, and Zhifeng Chen · 2020
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Accpar: Tensor partitioning for heterogeneous deep learning accelerators
Linghao Song, Fan Chen, Youwei Zhuo, Xuehai Qian, Hai Li, and Yiran Chen · 2020
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Supporting very large models using automatic dataflow graph partitioning
Minjie Wang, Chien-chin Huang, and Jinyang Li · 2019
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Megatron-LM: Training multi-billion parameter language models using model parallelism
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ChID: A large-scale Chinese IDiom dataset for cloze test
Chujie Zheng, Minlie Huang, and Aixin Sun · 2019
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A span-extraction dataset for Chinese machine reading comprehension
Yiming Cui, Ting Liu, Wanxiang Che, Li Xiao, Zhipeng Chen, Wentao Ma, Shijin Wang, and Guoping Hu · 2019
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Efficient algorithms for device placement of dnn graph operators
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Jay H. Park, Gyeongchan Yun, Chang M. Yi, Nguyen T. Nguyen, Seungmin Lee, Jaesik Choi, Sam H. Noh, and Young ri Choi · 2020
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A sentence cloze dataset for Chinese machine reading comprehension
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CLUE: A Chinese language understanding evaluation benchmark
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M6: A chinese multimodal pretrainer, 2021
Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, and Hongxia Yang · 2021
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DAPPLE: A pipelined data parallel approach for training large models
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Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity, 2021
William Fedus, Barret Zoph, and Noam Shazeer · 2021
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Learning transferable visual models from natural language supervision, 2021
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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