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Mixture of Robust Experts (MoRE): A Flexible Defense Against Multiple Perturbations


Apr 21, 2021
Hao Cheng, Kaidi Xu, Chenan Wang, Xue Lin, Bhavya Kailkhura, Ryan Goldhahn


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DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning


Apr 19, 2021
Yuting Gao, Jia-Xin Zhuang, Ke Li, Hao Cheng, Xiaowei Guo, Feiyue Huang, Rongrong Ji, Xing Sun


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Targeted Adversarial Training for Natural Language Understanding


Apr 12, 2021
Lis Pereira, Xiaodong Liu, Hao Cheng, Hoifung Poon, Jianfeng Gao, Ichiro Kobayashi

* 9 pages, 4 tables, 3 figurers, NAACL 2021 

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Orientation to Pose: Continuum Robots Shape Sensing Based on Piecewise Polynomial Curvature Model


Mar 09, 2021
Hao Cheng, Hongji Shang, Bin Lan, Houde Liu, Xueqian Wang, Bin Liang


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On The Consistency Training for Open-Set Semi-Supervised Learning


Jan 19, 2021
Huixiang Luo, Hao Cheng, Yuting Gao, Ke Li, Mengdan Zhang, Fanxu Meng, Xiaowei Guo, Feiyue Huang, Xing Sun

* 8 pages, 2 figures 

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Joint Dimensionality Reduction for Separable Embedding Estimation


Jan 14, 2021
Yanjun Li, Bihan Wen, Hao Cheng, Yoram Bresler


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UnitedQA: A Hybrid Approach for Open Domain Question Answering


Jan 01, 2021
Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao


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NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned


Jan 01, 2021
Sewon Min, Jordan Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih

* 26 pages 

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One for More: Selecting Generalizable Samples for Generalizable ReID Model


Dec 11, 2020
Enwei Zhang, Xinyang Jiang, Hao Cheng, Ancong Wu, Fufu Yu, Ke Li, Xiaowei Guo, Feng Zheng, Wei-Shi Zheng, Xing Sun


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Exploring Dynamic Context for Multi-path Trajectory Prediction


Nov 02, 2020
Hao Cheng, Wentong Liao, Xuejiao Tang, Michael Ying Yang, Monika Sester, Bodo Rosenhahn

* code available 

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Posterior Differential Regularization with f-divergence for Improving Model Robustness


Oct 23, 2020
Hao Cheng, Xiaodong Liu, Lis Pereira, Yaoliang Yu, Jianfeng Gao


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Pruning Filter in Filter


Oct 18, 2020
Fanxu Meng, Hao Cheng, Ke Li, Huixiang Luo, Xiaowei Guo, Guangming Lu, Xing Sun

* Accepted by NeurIPS2020 

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Learning with Instance-Dependent Label Noise: A Sample Sieve Approach


Oct 05, 2020
Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu


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Approximate Piecewise Constant Curvature Equivalent Model and Their Application to Continuum Robot Configuration Estimation


Sep 15, 2020
Hao Cheng, Houde Liu, Xueqian Wang, Bin Liang


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Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing


Aug 20, 2020
Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon


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Do Not Disturb Me: Person Re-identification Under the Interference of Other Pedestrians


Aug 16, 2020
Shizhen Zhao, Changxin Gao, Jun Zhang, Hao Cheng, Chuchu Han, Xinyang Jiang, Xiaowei Guo, Wei-Shi Zheng, Nong Sang, Xing Sun

* Accepted by ECCV 2020 

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Attentive Graph Neural Networks for Few-Shot Learning


Jul 14, 2020
Hao Cheng, Joey Tianyi Zhou, Wee Peng Tay, Bihan Wen


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AMENet: Attentive Maps Encoder Network for Trajectory Prediction


Jun 15, 2020
Hao Cheng, Wentong Liao, Michael Ying Yang, Bodo Rosenhahn, Monika Sester


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Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering


May 05, 2020
Hao Cheng, Ming-Wei Chang, Kenton Lee, Kristina Toutanova

* ACL2020 

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Adversarial Training for Large Neural Language Models


Apr 29, 2020
Xiaodong Liu, Hao Cheng, Pengcheng He, Weizhu Chen, Yu Wang, Hoifung Poon, Jianfeng Gao

* 13 pages, 9 tables, 2 figures 

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DGD: Densifying the Knowledge of Neural Networks with Filter Grafting and Knowledge Distillation


Apr 26, 2020
Hao Cheng, Fanxu Meng, Ke Li, Huixiang Luo, Guangming Lu, Xiaowei Guo, Feiyue Huang, Xing Sun


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MCENET: Multi-Context Encoder Network for Homogeneous Agent Trajectory Prediction in Mixed Traffic


Mar 03, 2020
Hao Cheng, Wentong Liao. Michael Ying Yang, Monika Sester, Bodo Rosenhahn

* 8 pages, 5 figures, code is available on https://github.com/haohao11/MCENET 

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Filter Grafting for Deep Neural Networks


Feb 26, 2020
Fanxu Meng, Hao Cheng, Ke Li, Zhixin Xu, Rongrong Ji, Xing Sun, Gaungming Lu

* Accepted by CVPR2020 

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Defending against Backdoor Attack on Deep Neural Networks


Feb 26, 2020
Hao Cheng, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Pu Zhao, Xue Lin

* Accepted by KDD 2019 AdvML workshop 

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The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding


Feb 19, 2020
Xiaodong Liu, Yu Wang, Jianshu Ji, Hao Cheng, Xueyun Zhu, Emmanuel Awa, Pengcheng He, Weizhu Chen, Hoifung Poon, Guihong Cao, Jianfeng Gao

* 9 pages, 3 figures and 3 tables 

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