Yehui Tang

According to our database, Yehui Tang authored at least 79 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

PocketLLM: Ultimate Compression of Large Language Models via Meta Networks.

Ye Tian, Chengcheng Wang, Jing Han, Yehui Tang, Kai Han

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

GenVidBench: A 6-Million Benchmark for AI-Generated Video Detection.

Zhenliang Ni, Qiangyu Yan, Mouxiao Huang, Tianning Yuan, Yehui Tang, Hailin Hu, Xinghao Chen, Yunhe Wang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

ScaleNet: Scaling up Pretrained Neural Networks with Incremental Parameters.

Zhiwei Hao, Jianyuan Guo, Li Shen, Kai Han, Yehui Tang, Han Hu, Yunhe Wang

CoRR, October, 2025

EAQuant: Enhancing Post-Training Quantization for MoE Models via Expert-Aware Optimization.

Zhongqian Fu, Ning Ding, Kai Han, Xianzhi Yu, Xiaosong Li, Xinghao Chen, Yehui Tang, Yunhe Wang

CoRR, June, 2025

Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity.

Yehui Tang, Xiaosong Li, Fangcheng Liu, Wei Guo, Hang Zhou, Yaoyuan Wang, Kai Han, Xianzhi Yu, Jinpeng Li, Hui Zang, Fei Mi, Xiaojun Meng, Zhicheng Liu, Hanting Chen, Binfan Zheng, Can Chen, Youliang Yan, Ruiming Tang, Peifeng Qin, Xinghao Chen, Dacheng Tao, Yunhe Wang

CoRR, May, 2025

Pangu Light: Weight Re-Initialization for Pruning and Accelerating LLMs.

Hanting Chen, Jiarui Qin, Jialong Guo, Tao Yuan, Yichun Yin, Huiling Zhen, Yasheng Wang, Jinpeng Li, Xiaojun Meng, Meng Zhang, Rongju Ruan, Zheyuan Bai, Yehui Tang, Can Chen, Xinghao Chen, Fisher Yu, Ruiming Tang, Yunhe Wang

CoRR, May, 2025

Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs.

Yehui Tang, Yichun Yin, Yaoyuan Wang, Hang Zhou, Yu Pan, Wei Guo, Zhiguo Zhang, Miao Rang, Fangcheng Liu, Naifu Zhang, Binghan Li, Yonghan Dong, Xiaojun Meng, Yasheng Wang, Dong Li, Yin Li, Dandan Tu, Can Chen, Youliang Yan, Fisher Yu, Ruiming Tang, Yunhe Wang, Botian Huang, Bo Wang, Boxiao Liu, Changzheng Zhang, Da Kuang, Fei Liu, Gang Huang, Jiansheng Wei, Jiarui Qin, Jie Ran, Jinpeng Li, Jun Zhao, Liang Dai, Lin Li, Liqun Deng, Peifeng Qin, Pengyuan Zeng, Qiang Gu, Shaohua Tang, Shengjun Cheng, Tao Gao, Tao Yu, Tianshu Li, Tianyu Bi, Wei He, Weikai Mao, Wenyong Huang, Wulong Liu, Xiabing Li, Xianzhi Yu, Xueyu Wu, Xu He, Yangkai Du, Yan Xu, Ye Tian, Yimeng Wu, Yongbing Huang, Yong Tian, Yong Zhu, Yue Li, Yufei Wang, Yuhang Gai, Yujun Li, Yu Luo, Yunsheng Ni, Yusen Sun, Zelin Chen, Zhe Liu, Zhicheng Liu, Zhipeng Tu, Zilin Ding, Zongyuan Zhan

CoRR, May, 2025

Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUs.

Yichun Yin, Wenyong Huang, Kaikai Song, Yehui Tang, Xueyu Wu, Wei Guo, Peng Guo, Yaoyuan Wang, Xiaojun Meng, Yasheng Wang, Dong Li, Can Chen, Dandan Tu, Yin Li, Fisher Yu, Ruiming Tang, Yunhe Wang, Baojun Wang, Bin Wang, Bo Wang, Boxiao Liu, Changzheng Zhang, Duyu Tang, Fei Mi, Hui Jin, Jiansheng Wei, Jiarui Qin, Jinpeng Li, Jun Zhao, Liqun Deng, Lin Li, Minghui Xu, Naifu Zhang, Nianzu Zheng, Qiang Li, Rongju Ruan, Shengjun Cheng, Tianyu Guo, Wei He, Wei Li, Weiwen Liu, Wulong Liu, Xinyi Dai, Yonghan Dong, Yu Pan, Yue Li, Yufei Wang, Yujun Li, Yunsheng Ni, Zhe Liu, Zhenhe Zhang, Zhicheng Liu

CoRR, April, 2025

Saliency-driven Dynamic Token Pruning for Large Language Models.

Yao Tao, Yehui Tang, Yun Wang, Mingjian Zhu, Hailin Hu, Yunhe Wang

CoRR, April, 2025

Post-Training Quantization for Diffusion Transformer via Hierarchical Timestep Grouping.

Ning Ding, Jing Han, Yuchuan Tian, Chao Xu, Kai Han, Yehui Tang

CoRR, March, 2025

GenVidBench: A Challenging Benchmark for Detecting AI-Generated Video.

Zhenliang Ni, Qiangyu Yan, Mouxiao Huang, Tianning Yuan, Yehui Tang, Hailin Hu, Xinghao Chen, Yunhe Wang

CoRR, January, 2025

ScaleNet: Scaling up Pretrained Neural Networks With Incremental Parameters.

Zhiwei Hao, Jianyuan Guo, Li Shen, Kai Han, Yehui Tang, Han Hu, Yunhe Wang

IEEE Trans. Image Process., 2025

GPT4Image: Large Pre-trained Models Help Vision Models Learn Better on Perception Task.

Ning Ding, Yehui Tang, Zhongqian Fu, Chao Xu, Kai Han, Yunhe Wang

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

EMS-SD: Efficient Multi-sample Speculative Decoding for Accelerating Large Language Models.

Yunsheng Ni, Chuanjian Liu, Yehui Tang, Kai Han, Yunhe Wang

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

DenseSSM: State Space Models with Dense Hidden Connection for Efficient Large Language Models.

Wei He, Kai Han, Yehui Tang, Chengcheng Wang, Yujie Yang, Tianyu Guo, Yunhe Wang

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Mixture of Lookup Experts.

Shibo Jie, Yehui Tang, Kai Han, Yitong Li, Duyu Tang, Zhi-Hong Deng, Yunhe Wang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

SpeCache: Speculative Key-Value Caching for Efficient Generation of LLMs.

Shibo Jie, Yehui Tang, Kai Han, Zhi-Hong Deng, Jing Han

Proceedings of the Forty-second International Conference on Machine Learning, 2025

SlimLLM: Accurate Structured Pruning for Large Language Models.

Jialong Guo, Xinghao Chen, Yehui Tang, Yunhe Wang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning.

Zhenni Bi, Kai Han, Chuanjian Liu, Yehui Tang, Yunhe Wang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

LLM Data Selection and Utilization via Dynamic Bi-level Optimization.

Yang Yu, Kai Han, Hang Zhou, Yehui Tang, Kaiqi Huang, Yunhe Wang, Dacheng Tao

Proceedings of the Forty-second International Conference on Machine Learning, 2025

CBQ: Cross-Block Quantization for Large Language Models.

Xin Ding, Xiaoyu Liu, Zhijun Tu, Yun Zhang, Wei Li, Jie Hu, Hanting Chen, Yehui Tang, Zhiwei Xiong, Baoqun Yin, Yunhe Wang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

TinySAM: Pushing the Envelope for Efficient Segment Anything Model.

Han Shu, Wenshuo Li, Yehui Tang, Yiman Zhang, Yihao Chen, Houqiang Li, Yunhe Wang, Xinghao Chen

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

Eve: Efficient Multimodal Vision Language Models with Elastic Visual Experts.

Miao Rang, Zhenni Bi, Chuanjian Liu, Yehui Tang, Kai Han, Yunhe Wang

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMs.

Kai Han, Jianyuan Guo, Yehui Tang, Wei He, Enhua Wu, Yunhe Wang

CoRR, 2024

Multi-Granularity Semantic Revision for Large Language Model Distillation.

Xiaoyu Liu, Yun Zhang, Wei Li, Simiao Li, Xudong Huang, Hanting Chen, Yehui Tang, Jie Hu, Zhiwei Xiong, Yunhe Wang

CoRR, 2024

No Time to Waste: Squeeze Time into Channel for Mobile Video Understanding.

Yingjie Zhai, Wenshuo Li, Yehui Tang, Xinghao Chen, Yunhe Wang

CoRR, 2024

Kangaroo: Lossless Self-Speculative Decoding via Double Early Exiting.

Fangcheng Liu, Yehui Tang, Zhenhua Liu, Yunsheng Ni, Kai Han, Yunhe Wang

CoRR, 2024

GhostNetV3: Exploring the Training Strategies for Compact Models.

Zhenhua Liu, Zhiwei Hao, Kai Han, Yehui Tang, Yunhe Wang

CoRR, 2024

DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models.

Wei He, Kai Han, Yehui Tang, Chengcheng Wang, Yujie Yang, Tianyu Guo, Yunhe Wang

CoRR, 2024

SAM-DiffSR: Structure-Modulated Diffusion Model for Image Super-Resolution.

Chengcheng Wang, Zhiwei Hao, Yehui Tang, Jianyuan Guo, Yujie Yang, Kai Han, Yunhe Wang

CoRR, 2024

A Survey on Transformer Compression.

Yehui Tang, Yunhe Wang, Jianyuan Guo, Zhijun Tu, Kai Han, Hailin Hu, Dacheng Tao

CoRR, 2024

Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning.

Hang Zhou, Yehui Tang, Haochen Qin, Yujie Yang, Renren Jin, Deyi Xiong, Kai Han, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exiting.

Fangcheng Liu, Yehui Tang, Zhenhua Liu, Yunsheng Ni, Duyu Tang, Kai Han, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers.

Ning Ding, Yehui Tang, Haochen Qin, Zhenli Zhou, Chao Xu, Lin Li, Kai Han, Heng Liao, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Rethinking Optimization and Architecture for Tiny Language Models.

Yehui Tang, Kai Han, Fangcheng Liu, Yunsheng Ni, Yuchuan Tian, Zheyuan Bai, Yi-Qi Hu, Sichao Liu, Shangling Jui, Yunhe Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking.

Wenshuo Li, Xinghao Chen, Han Shu, Yehui Tang, Yunhe Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning.

Shibo Jie, Yehui Tang, Ning Ding, Zhi-Hong Deng, Kai Han, Yunhe Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Data-efficient Large Vision Models through Sequential Autoregression.

Zhiwei Hao, Jianyuan Guo, Chengcheng Wang, Yehui Tang, Han Wu, Han Hu, Kai Han, Chang Xu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization.

Jialong Guo, Xinghao Chen, Yehui Tang, Yunhe Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Adapt Without Forgetting: Distill Proximity from Dual Teachers in Vision-Language Models.

Mengyu Zheng, Yehui Tang, Zhiwei Hao, Kai Han, Yunhe Wang, Chang Xu

Proceedings of the Computer Vision - ECCV 2024, 2024

Visual Prompting via Partial Optimal Transport.

Mengyu Zheng, Zhiwei Hao, Yehui Tang, Chang Xu

Proceedings of the Computer Vision - ECCV 2024, 2024

Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation.

Zhenliang Ni, Xinghao Chen, Yingjie Zhai, Yehui Tang, Yunhe Wang

Proceedings of the Computer Vision - ECCV 2024, 2024

Token Compensator: Altering Inference Cost of Vision Transformer Without Re-tuning.

Shibo Jie, Yehui Tang, Jianyuan Guo, Zhi-Hong Deng, Kai Han, Yunhe Wang

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

A Survey on Vision Transformer.

Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, Dacheng Tao

IEEE Trans. Pattern Anal. Mach. Intell., 2023

PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation.

Yunhe Wang, Hanting Chen, Yehui Tang, Tianyu Guo, Kai Han, Ying Nie, Xutao Wang, Hailin Hu, Zheyuan Bai, Yun Wang, Fangcheng Liu, Zhicheng Liu, Jianyuan Guo, Sinan Zeng, Yinchen Zhang, Qinghua Xu, Qun Liu, Jun Yao, Chao Xu, Dacheng Tao

CoRR, 2023

LightCLIP: Learning Multi-Level Interaction for Lightweight Vision-Language Models.

Ying Nie, Wei He, Kai Han, Yehui Tang, Tianyu Guo, Fanyi Du, Yunhe Wang

CoRR, 2023

GPT4Image: Can Large Pre-trained Models Help Vision Models on Perception Tasks?

Ning Ding, Yehui Tang, Zhongqian Fu, Chao Xu, Kai Han, Yunhe Wang

CoRR, 2023

One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation.

Zhiwei Hao, Jianyuan Guo, Kai Han, Yehui Tang, Han Hu, Yunhe Wang, Chang Xu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Masked Image Modeling with Local Multi-Scale Reconstruction.

Haoqing Wang, Yehui Tang, Yunhe Wang, Jianyuan Guo, Zhi-Hong Deng, Kai Han

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Network Expansion For Practical Training Acceleration.

Ning Ding, Yehui Tang, Kai Han, Chao Xu, Yunhe Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

FastMIM: Expediting Masked Image Modeling Pre-training for Vision.

Jianyuan Guo, Kai Han, Han Wu, Yehui Tang, Yunhe Wang, Chang Xu

CoRR, 2022

PyramidTNT: Improved Transformer-in-Transformer Baselines with Pyramid Architecture.

Kai Han, Jianyuan Guo, Yehui Tang, Yunhe Wang

CoRR, 2022

GhostNetV2: Enhance Cheap Operation with Long-Range Attention.

Yehui Tang, Kai Han, Jianyuan Guo, Chang Xu, Chao Xu, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation.

Zhiwei Hao, Jianyuan Guo, Ding Jia, Kai Han, Yehui Tang, Chao Zhang, Han Hu, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bridge the Gap Between Architecture Spaces via A Cross-Domain Predictor.

Yuqiao Liu, Yehui Tang, Zeqiong Lv, Yunhe Wang, Yanan Sun

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Vision GNN: An Image is Worth Graph of Nodes.

Kai Han, Yunhe Wang, Jianyuan Guo, Yehui Tang, Enhua Wu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Spatial-Channel Token Distillation for Vision MLPs.

Yanxi Li, Xinghao Chen, Minjing Dong, Yehui Tang, Yunhe Wang, Chang Xu

Proceedings of the International Conference on Machine Learning, 2022

An Image Patch is a Wave: Phase-Aware Vision MLP.

Yehui Tang, Kai Han, Jianyuan Guo, Chang Xu, Yanxi Li, Chao Xu, Yunhe Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Patch Slimming for Efficient Vision Transformers.

Yehui Tang, Kai Han, Yunhe Wang, Chang Xu, Jianyuan Guo, Chao Xu, Dacheng Tao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Hire-MLP: Vision MLP via Hierarchical Rearrangement.

Jianyuan Guo, Yehui Tang, Kai Han, Xinghao Chen, Han Wu, Chao Xu, Chang Xu, Yunhe Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

CMT: Convolutional Neural Networks Meet Vision Transformers.

Jianyuan Guo, Kai Han, Han Wu, Yehui Tang, Xinghao Chen, Yunhe Wang, Chang Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Source-Free Domain Adaptation via Distribution Estimation.

Ning Ding, Yixing Xu, Yehui Tang, Chao Xu, Yunhe Wang, Dacheng Tao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

CMT: Convolutional Neural Networks Meet Vision Transformers.

Jianyuan Guo, Kai Han, Han Wu, Chang Xu, Yehui Tang, Chunjing Xu, Yunhe Wang

CoRR, 2021

Efficient Vision Transformers via Fine-Grained Manifold Distillation.

Ding Jia, Kai Han, Yunhe Wang, Yehui Tang, Jianyuan Guo, Chao Zhang, Dacheng Tao

CoRR, 2021

Visual Transformer Pruning.

Mingjian Zhu, Kai Han, Yehui Tang, Yunhe Wang

CoRR, 2021

Learning Frequency Domain Approximation for Binary Neural Networks.

Yixing Xu, Kai Han, Chang Xu, Yehui Tang, Chunjing Xu, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Augmented Shortcuts for Vision Transformers.

Yehui Tang, Kai Han, Chang Xu, An Xiao, Yiping Deng, Chao Xu, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Homogeneous Architecture Augmentation for Neural Predictor.

Yuqiao Liu, Yehui Tang, Yanan Sun

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

ReNAS: Relativistic Evaluation of Neural Architecture Search.

Yixing Xu, Yunhe Wang, Kai Han, Yehui Tang, Shangling Jui, Chunjing Xu, Chang Xu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Manifold Regularized Dynamic Network Pruning.

Yehui Tang, Yunhe Wang, Yixing Xu, Yiping Deng, Chao Xu, Dacheng Tao, Chang Xu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

A Survey on Visual Transformer.

Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, Dacheng Tao

CoRR, 2020

SCOP: Scientific Control for Reliable Neural Network Pruning.

Yehui Tang, Yunhe Wang, Yixing Xu, Dacheng Tao, Chunjing Xu, Chao Xu, Chang Xu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Semi-Supervised Assessor of Neural Architectures.

Yehui Tang, Yunhe Wang, Yixing Xu, Hanting Chen, Boxin Shi, Chao Xu, Chunjing Xu, Qi Tian, Chang Xu

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Neuromorphic Camera Guided High Dynamic Range Imaging.

Jin Han, Chu Zhou, Peiqi Duan, Yehui Tang, Chang Xu, Chao Xu, Tiejun Huang, Boxin Shi

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Frequency Domain Compact 3D Convolutional Neural Networks.

Hanting Chen, Yunhe Wang, Han Shu, Yehui Tang, Chunjing Xu, Boxin Shi, Chao Xu, Qi Tian, Chang Xu

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Reborn Filters: Pruning Convolutional Neural Networks with Limited Data.

Yehui Tang, Shan You, Chang Xu, Jin Han, Chen Qian, Boxin Shi, Chao Xu, Changshui Zhang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks.

Yehui Tang, Yunhe Wang, Yixing Xu, Boxin Shi, Chao Xu, Chunjing Xu, Chang Xu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

RNAS: Architecture Ranking for Powerful Networks.

Yixing Xu, Yunhe Wang, Kai Han, Hanting Chen, Yehui Tang, Shangling Jui, Chunjing Xu, Qi Tian, Chang Xu

CoRR, 2019

Bringing Giant Neural Networks Down to Earth with Unlabeled Data.

Yehui Tang, Shan You, Chang Xu, Boxin Shi, Chao Xu

CoRR, 2019