Yue Guan

According to our database, Yue Guan authored at least 27 papers between 2020 and 2026.

Collaborative distances:

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

2026

TLX: Hardware-Native, Evolvable MIMW GPU Compiler for Large-scale Production Environments.

Yue Guan, Hongtao Yu, Peng Chen, Daohang Shi, Karthik Manivannan, Nicholas J. Riasanovsky, Manman Ren, Lei Wang, Shane Nay, Partha Kanuparthy, Zaifeng Pan, Zhengding Hu, Yufei Ding

CoRR, May, 2026

FlashEvolve: Accelerating Agent Self-Evolution with Asynchronous Stage Orchestration.

Zhengding Hu, Mingge Lu, Zhen Wang, Jixuan Ruan, Chang Chen, Zaifeng Pan, Yue Guan, Ruiyi Wang, Zhongkai Yu, Chao Zhang, Yufei Ding

CoRR, May, 2026

JigsawRL: Assembling RL Pipelines for Efficient LLM Post-Training.

Zhengding Hu, Hehua Ouyang, Chang Chen, Zaifeng Pan, Yue Guan, Zhongkai Yu, Zhen Wang, Steven Swanson, Yufei Ding

CoRR, April, 2026

Pancake: Hierarchical Memory System for Multi-Agent LLM Serving.

Zhengding Hu, Zaifeng Pan, Prabhleen Kaur, Vibha Murthy, Zhongkai Yu, Yue Guan, Zhen Wang, Steven Swanson, Yufei Ding

CoRR, February, 2026

ScaleSim: Serving Large-Scale Multi-Agent Simulation with Invocation Distance-Based Memory Management.

Zaifeng Pan, Yipeng Shen, Zhengding Hu, Zhuang Wang, Aninda Manocha, Zheng Wang, Zhongkai Yu, Yue Guan, Yufei Ding

CoRR, January, 2026

AutoOverlap: Enabling Fine-Grained Overlap of Computation and Communication with Chunk-Based Scheduling.

Xinwei Qiang, Yue Guan, Zhengding Hu, Yufei Ding, Adnan Aziz

CoRR, January, 2026

Proton: Towards Multi-level, Adaptive Profiling for Triton.

Keren Zhou, Tianle Zhong, Hao Wu, Jihyeong Lee, Yue Guan, Yufei Ding, Corbin Robeck, Yuanwei Fang, Jeff Niu, Philippe Tillet

Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2026

2025

Orders in Chaos: Enhancing Large-Scale MoE LLM Serving with Data Movement Forecasting.

Zhongkai Yu, Yue Guan, Zihao Yu, Chenyang Zhou, Shuyi Pei, Yangwook Kang, Yufei Ding, Po-An Tsai

CoRR, October, 2025

KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads.

Yue Guan, Yuanwei Fang, Keren Zhou, Corbin Robeck, Manman Ren, Zhongkai Yu, Yufei Ding, Adnan Aziz

CoRR, May, 2025

Mercury: Unlocking Multi-GPU Operator Optimization for LLMs via Remote Memory Scheduling.

Yue Guan, Xinwei Qiang, Zaifeng Pan, Daniels Johnson, Yuanwei Fang, Keren Zhou, Yuke Wang, Wanlu Li, Yufei Ding, Adnan Aziz

Proceedings of the ACM SIGOPS 31st Symposium on Operating Systems Principles, 2025

KPerfIR: Towards a Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads.

Yue Guan, Yuanwei Fang, Keren Zhou, Corbin Robeck, Manman Ren, Zhongkai Yu, Yufei Ding, Adnan Aziz

Proceedings of the 19th USENIX Symposium on Operating Systems Design and Implementation, 2025

WLB-LLM: Workload-Balanced 4D Parallelism for Large Language Model Training.

Zheng Wang, Anna Cai, Xinfeng Xie, Zaifeng Pan, Yue Guan, Weiwei Chu, Jie Wang, Shikai Li, Jianyu Huang, Chris Cai, Yuchen Hao, Yufei Ding

Proceedings of the 19th USENIX Symposium on Operating Systems Design and Implementation, 2025

KVFlow: Efficient Prefix Caching for Accelerating LLM-Based Multi-Agent Workflows.

Zaifeng Pan, Ajjkumar Patel, Yipeng Shen, Zhengding Hu, Yue Guan, Wan-Lu Li, Lianhui Qin, Yida Wang, Yufei Ding

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Yggdrasil: Bridging Dynamic Speculation and Static Runtime for Latency-Optimal Tree-Based LLM Decoding.

Yue Guan, Changming Yu, Shihan Fang, Weiming Hu, Zaifeng Pan, Zheng Wang, Zihan Liu, Yangjie Zhou, Yufei Ding, Minyi Guo, Jingwen Leng

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

FastTree: Optimizing Attention Kernel and Runtime for Tree-Structured LLM Inference.

Zaifeng Pan, Yitong Ding, Yue Guan, Zheng Wang, Zhongkai Yu, Xulong Tang, Yida Wang, Yufei Ding

Proceedings of the Eighth Conference on Machine Learning and Systems, 2025

An Efficient Private GPT Never Autoregressively Decodes.

Zhengyi Li, Yue Guan, Kang Yang, Yu Feng, Ning Liu, Yu Yu, Jingwen Leng, Minyi Guo

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

M-ANT: Efficient Low-bit Group Quantization for LLMs via Mathematically Adaptive Numerical Type.

Weiming Hu, Haoyan Zhang, Cong Guo, Yu Feng, Renyang Guan, Zhendong Hua, Zihan Liu, Yue Guan, Minyi Guo, Jingwen Leng

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2025

VQ-LLM: High-performance Code Generation for Vector Quantization Augmented LLM Inference.

Zihan Liu, Xinhao Luo, Junxian Guo, Wentao Ni, Yangjie Zhou, Yue Guan, Cong Guo, Weihao Cui, Yu Feng, Minyi Guo, Yuhao Zhu, Minjia Zhang, Chen Jin, Jingwen Leng

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2025

2024

Accelerating Sparse DNNs Based on Tiled GEMM.

Cong Guo, Fengchen Xue, Jingwen Leng, Yuxian Qiu, Yue Guan, Weihao Cui, Quan Chen, Minyi Guo

IEEE Trans. Computers, May, 2024

Fractal: Joint Multi-Level Sparse Pattern Tuning of Accuracy and Performance for DNN Pruning.

Yue Guan, Changming Yu, Yangjie Zhou, Jingwen Leng, Chao Li, Minyi Guo

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

Amanda: Unified Instrumentation Framework for Deep Neural Networks.

Yue Guan, Yuxian Qiu, Jingwen Leng, Fan Yang, Shuo Yu, Yunxin Liu, Yu Feng, Yuhao Zhu, Lidong Zhou, Yun Liang, Chen Zhang, Chao Li, Minyi Guo

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2022

PAME: precision-aware multi-exit DNN serving for reducing latencies of batched inferences.

Shulai Zhang, Weihao Cui, Quan Chen, Zhengnian Zhang, Yue Guan, Jingwen Leng, Chao Li, Minyi Guo

Proceedings of the ICS '22: 2022 International Conference on Supercomputing, Virtual Event, June 28, 2022

Transkimmer: Transformer Learns to Layer-wise Skim.

Yue Guan, Zhengyi Li, Jingwen Leng, Zhouhan Lin, Minyi Guo

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Block-Skim: Efficient Question Answering for Transformer.

Yue Guan, Zhengyi Li, Zhouhan Lin, Yuhao Zhu, Jingwen Leng, Minyi Guo

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2020

Co-Design of Binary Processing in Memory ReRAM Array and DNN Model Optimization Algorithm.

Yue Guan, Takashi Ohsawa

IEICE Trans. Electron., 2020

Accelerating sparse DNN models without hardware-support via tile-wise sparsity.

Cong Guo, Bo Yang Hsueh, Jingwen Leng, Yuxian Qiu, Yue Guan, Zehuan Wang, Xiaoying Jia, Xipeng Li, Minyi Guo, Yuhao Zhu

Proceedings of the International Conference for High Performance Computing, 2020

How Far Does BERT Look At: Distance-based Clustering and Analysis of BERT's Attention.

Yue Guan, Jingwen Leng, Chao Li, Quan Chen, Minyi Guo

Proceedings of the 28th International Conference on Computational Linguistics, 2020