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PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance



Qingru Zhang , Simiao Zuo , Chen Liang , Alexander Bukharin , Pengcheng He , Weizhu Chen , Tuo Zhao

* Proceedings of the 39th International Conference on Machine Learning (ICML 2022) 

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GODEL: Large-Scale Pre-Training for Goal-Directed Dialog



Baolin Peng , Michel Galley , Pengcheng He , Chris Brockett , Lars Liden , Elnaz Nouri , Zhou Yu , Bill Dolan , Jianfeng Gao


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Diffusion-GAN: Training GANs with Diffusion



Zhendong Wang , Huangjie Zheng , Pengcheng He , Weizhu Chen , Mingyuan Zhou


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ALLSH: Active Learning Guided by Local Sensitivity and Hardness



Shujian Zhang , Chengyue Gong , Xingchao Liu , Pengcheng He , Weizhu Chen , Mingyuan Zhou

* NAACL 2022 (finding); Our code is publicly available at https://github.com/szhang42/allsh 

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MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation



Simiao Zuo , Qingru Zhang , Chen Liang , Pengcheng He , Tuo Zhao , Weizhu Chen

* NAACL 2022 

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CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing



Chen Liang , Pengcheng He , Yelong Shen , Weizhu Chen , Tuo Zhao

* Proceedings of ACL 2022 

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Truncated Diffusion Probabilistic Models



Huangjie Zheng , Pengcheng He , Weizhu Chen , Mingyuan Zhou


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No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models



Chen Liang , Haoming Jiang , Simiao Zuo , Pengcheng He , Xiaodong Liu , Jianfeng Gao , Weizhu Chen , Tuo Zhao

* Proceedings of ICLR 2022 

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