Xianzhi Yu

According to our database, Xianzhi Yu authored at least 24 papers between 2020 and 2025.

Collaborative distances:

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

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

A Simple Linear Patch Revives Layer-Pruned Large Language Models.

Xinrui Chen, Haoli Bai, Tao Yuan, Ruikang Liu, Kang Zhao, Xianzhi Yu, Lu Hou, Tian Guan, Yonghong He, Chun Yuan

CoRR, May, 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

MoESD: Unveil Speculative Decoding's Potential for Accelerating Sparse MoE.

Zongle Huang, Lei Zhu, Zongyuan Zhan, Ting Hu, Weikai Mao, Xianzhi Yu, Yongpan Liu, Tianyu Zhang

CoRR, May, 2025

Faster and Better LLMs via Latency-Aware Test-Time Scaling.

Zili Wang, Tianyu Zhang, Lei Zhu, Haoli Bai, Lu Hou, Shiming Xiang, Xianzhi Yu, Wulong Liu

CoRR, May, 2025

PreMoe: Lightening MoEs on Constrained Memory by Expert Pruning and Retrieval.

Zehua Pei, Yingchun Zhang, Hui-Ling Zhen, Xianzhi Yu, Wulong Liu, Sinno Jialin Pan, Mingxuan Yuan, Bei Yu

CoRR, May, 2025

L-MTP: Leap Multi-Token Prediction Beyond Adjacent Context for Large Language Models.

Xiaohao Liu, Xiaobo Xia, Weixiang Zhao, Manyi Zhang, Xianzhi Yu, Xiu Su, Shuo Yang, See-Kiong Ng, Tat-Seng Chua

CoRR, May, 2025

TrimR: Verifier-based Training-Free Thinking Compression for Efficient Test-Time Scaling.

Weizhe Lin, Xing Li, Zhiyuan Yang, Xiaojin Fu, Hui-Ling Zhen, Yaoyuan Wang, Xianzhi Yu, Wulong Liu, Xiaosong Li, Mingxuan Yuan

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

Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models.

Ruikang Liu, Yuxuan Sun, Manyi Zhang, Haoli Bai, Xianzhi Yu, Tiezheng Yu, Chun Yuan, Lu Hou

CoRR, April, 2025

SVDq: 1.25-bit and 410x Key Cache Compression for LLM Attention.

Hong Yankun, Xing Li, Hui-Ling Zhen, Xianzhi Yu, Wulong Liu, Mingxuan Yuan

CoRR, February, 2025

CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference.

Zehua Pei, Lancheng Zou, Hui-Ling Zhen, Xianzhi Yu, Wulong Liu, Sinno Jialin Pan, Mingxuan Yuan, Bei Yu

CoRR, February, 2025

AttentionPredictor: Temporal Pattern Matters for Efficient LLM Inference.

Qingyue Yang, Jie Wang, Xing Li, Zhihai Wang, Chen Chen, Lei Chen, Xianzhi Yu, Wulong Liu, Jianye Hao, Mingxuan Yuan, Bin Li

CoRR, February, 2025

2024

LO-SpMM: Low-cost Search for High-performance SpMM Kernels on GPUs.

Junqing Lin, Jingwei Sun, Xiaolong Shi, Honghe Zhang, Xianzhi Yu, Xinzhi Wang, Jun Yao, Guangzhong Sun

ACM Trans. Archit. Code Optim., December, 2024

FuseGPT: Learnable Layers Fusion of Generative Pre-trained Transformers.

Zehua Pei, Hui-Ling Zhen, Xianzhi Yu, Sinno Jialin Pan, Mingxuan Yuan, Bei Yu

CoRR, 2024

FastAttention: Extend FlashAttention2 to NPUs and Low-resource GPUs.

Haoran Lin, Xianzhi Yu, Kang Zhao, Lu Hou, Zongyuan Zhan, Stanislav Kamenev, Han Bao, Ting Hu, Mingkai Wang, Qixin Chang, Siyue Sui, Weihao Sun, Jiaxin Hu, Jun Yao, Zekun Yin, Cheng Qian, Ying Zhang, Yinfei Pan, Yu Yang, Weiguo Liu

CoRR, 2024

FlatQuant: Flatness Matters for LLM Quantization.

Yuxuan Sun, Ruikang Liu, Haoli Bai, Han Bao, Kang Zhao, Yuening Li, Jiaxin Hu, Xianzhi Yu, Lu Hou, Chun Yuan, Xin Jiang, Wulong Liu, Jun Yao

CoRR, 2024

2023

EC-SpMM: Efficient Compilation of SpMM Kernel on GPUs.

Junqing Lin, Honghe Zhang, Xiaolong Shi, Jingwei Sun, Xianzhi Yu, Jun Yao, Guangzhong Sun

Proceedings of the 52nd International Conference on Parallel Processing, 2023

2022

An Application-oblivious Memory Scheduling System for DNN Accelerators.

Jiansong Li, Xueying Wang, Xiaobing Chen, Guangli Li, Xiao Dong, Peng Zhao, Xianzhi Yu, Yongxin Yang, Wei Cao, Lei Liu, Xiaobing Feng

ACM Trans. Archit. Code Optim., 2022

HW-TSC's Submission for the WMT22 Efficiency Task.

Hengchao Shang, Ting Hu, Daimeng Wei, Zongyao Li, Xianzhi Yu, Jianfei Feng, Ting Zhu, Lizhi Lei, Shimin Tao, Hao Yang, Ying Qin, Jinlong Yang, Zhiqiang Rao, Zhengzhe Yu

Proceedings of the Seventh Conference on Machine Translation, 2022

Accelerating Sparse Convolution with Column Vector-Wise Sparsity.

Yijun Tan, Kai Han, Kang Zhao, Xianzhi Yu, Zidong Du, Yunji Chen, Yunhe Wang, Jun Yao

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

2021

Optimizing the LINPACK Algorithm for Large-Scale PCIe-Based CPU-GPU Heterogeneous Systems.

Guangming Tan, Chaoyang Shui, Yinshan Wang, Xianzhi Yu, Yujin Yan

IEEE Trans. Parallel Distributed Syst., 2021

Pinpointing the Memory Behaviors of DNN Training.

Jiansong Li, Xiao Dong, Guangli Li, Peng Zhao, Xueying Wang, Xiaobing Chen, Xianzhi Yu, Yongxin Yang, Zihan Jiang, Wei Cao, Lei Liu, Xiaobing Feng

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2021

2020

Revisiting linpack algorithm on large-scale CPU-GPU heterogeneous systems.

Chaoyang Shui, Xianzhi Yu, Yujin Yan, Yinshan Wang, Ke Meng, Guangming Tan

Proceedings of the PPoPP '20: 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2020