Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs. - Minjie Wang; Lingfan Yu; Da Zheng; Quan Gan; Yu Gai; Zihao Ye 001; Mufei Li; Jinjing Zhou; Qi Huang 001; Chao Ma 025; Ziyue Huang; Qipeng Guo; et al. (CoRR, 2019)

BP-Transformer: Modelling Long-Range Context via Binary Partitioning. - Zihao Ye 001; Qipeng Guo; Quan Gan; Xipeng Qiu; Zheng Zhang 001 (CoRR, 2019)

FeatGraph: a flexible and efficient backend for graph neural network systems. - Yuwei Hu; Zihao Ye 001; Minjie Wang; Jiali Yu; Da Zheng; Mu Li 003; Zheng Zhang 001; Zhiru Zhang; Yida Wang 003 (SC, 2020)

DGL-KE: Training Knowledge Graph Embeddings at Scale. - Da Zheng; Xiang Song 003; Chao Ma 025; Zeyuan Tan; Zihao Ye 001; Jin Dong; Hao Xiong; Zheng Zhang 001; George Karypis (SIGIR, 2020)

Transformer on a Diet. - Chenguang Wang 001; Zihao Ye 001; Aston Zhang; Zheng Zhang 001; Alexander J. Smola (CoRR, 2020)

Graphiler: Optimizing Graph Neural Networks with Message Passing Data Flow Graph. - Zhiqiang Xie; Minjie Wang; Zihao Ye 001; Zheng Zhang 001; Rui Fan (MLSys, 2022)

TensorIR: An Abstraction for Automatic Tensorized Program Optimization. - Siyuan Feng; Bohan Hou; Hongyi Jin; Wuwei Lin; Junru Shao; Ruihang Lai; Zihao Ye 001; Lianmin Zheng; Cody Hao Yu; Yong Yu 001; Tianqi Chen 001 (ASPLOS (2), 2023)

SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning. - Zihao Ye 001; Ruihang Lai; Junru Shao; Tianqi Chen 001; Luis Ceze (ASPLOS (3), 2023)

vMCU: Coordinated Memory Management and Kernel Optimization for DNN Inference on MCUs. - Size Zheng 001; Renze Chen; Meng Li 004; Zihao Ye 001; Luis Ceze; Yun Liang 001 (MLSys, 2024)

Punica: Multi-Tenant LoRA Serving. - Lequn Chen 001; Zihao Ye 001; Yongji Wu; Danyang Zhuo; Luis Ceze; Arvind Krishnamurthy (MLSys, 2024)

Atom: Low-Bit Quantization for Efficient and Accurate LLM Serving. - Yilong Zhao; Chien-Yu Lin; Kan Zhu; Zihao Ye 001; Lequn Chen 001; Size Zheng 001; Luis Ceze; Arvind Krishnamurthy; Tianqi Chen 001; Baris Kasikci (MLSys, 2024)

NanoFlow: Towards Optimal Large Language Model Serving Throughput. - Kan Zhu; Yilong Zhao; Liangyu Zhao; Gefei Zuo; Yile Gu; Dedong Xie; Yufei Gao; Qinyu Xu; Tian Tang; Zihao Ye 001; Keisuke Kamahori; Chien-Yu Lin; et al. (CoRR, 2024)

Relax: Composable Abstractions for End-to-End Dynamic Machine Learning. - Ruihang Lai; Junru Shao; Siyuan Feng; Steven Lyubomirsky; Bohan Hou; Wuwei Lin; Zihao Ye 001; Hongyi Jin; Yuchen Jin; Jiawei Liu 004; Lesheng Jin; Yaxing Cai; et al. (ASPLOS (2), 2025)

NanoFlow: Towards Optimal Large Language Model Serving Throughput. - Kan Zhu; Yufei Gao; Yilong Zhao; Liangyu Zhao; Gefei Zuo; Yile Gu; Dedong Xie; Zihao Ye 001; Keisuke Kamahori; Chien-Yu Lin; Ziren Wang; Stephanie Wang; et al. (OSDI, 2025)

FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving. - Zihao Ye 001; Lequn Chen 001; Ruihang Lai; Wuwei Lin; Yineng Zhang; Stephanie Wang; Tianqi Chen 001; Baris Kasikci; Vinod Grover; Arvind Krishnamurthy; Luis Ceze (CoRR, 2025)

TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval. - Chien-Yu Lin; Keisuke Kamahori; Yiyu Liu; Xiaoxiang Shi; Madhav Mahesh Kashyap; Yile Gu; Rulin Shao; Zihao Ye 001; Kan Zhu; Stephanie Wang; Arvind Krishnamurthy; Rohan Kadekodi; et al. (CoRR, 2025)