Hailin Zhang - RankMe

27 papers A* 3Journal 23Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Retrieval-Augmented Generation for AI-Generated Content: A Survey. Data Sci. Eng. Penghao Zhao, Hailin Zhang, Qinhan Yu, Zhengren Wang, Yunteng Geng, Fangcheng Fu, Ling Yang, Wentao Zhang, Jie Jiang, Bin Cui
2025	J	`jnl`	CAFE+: Towards Compact, Adaptive, and Fast Embedding for Large-scale Online Recommendation Models. ACM Trans. Inf. Syst. Zirui Liu, Hailin Zhang, Boxuan Chen, Zihan Jiang, Yikai Zhao, Yangyu Tao, Tong Yang, Bin Cui
2025	J	`jnl`	Efficient and scalable huge embedding model training via distributed cache management. VLDB J. Xupeng Miao, Hailin Zhang, Yining Shi, Xiaonan Nie, Zhi Yang, Yangyu Tao, Jie Jiang, Bin Cui
2025	J	`jnl`	MEMO: Fine-grained Tensor Management For Ultra-long Context LLM Training. Proc. ACM Manag. Data Pinxue Zhao, Hailin Zhang, Fangcheng Fu, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui
2025	J	`jnl`	Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization. Proc. ACM Manag. Data Haoyang Li, Fangcheng Fu, Hao Ge, Sheng Lin, Xuanyu Wang, Jiawen Niu, Yujie Wang, Hailin Zhang, Xiaonan Nie, Bin Cui
2025	J	`jnl`	PQCache: Product Quantization-based KVCache for Long Context LLM Inference. Proc. ACM Manag. Data Hailin Zhang, Xiaodong Ji, Yilin Chen, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Weipeng Chen, Bin Cui
2025	J	`jnl`	SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling. CoRR Xiaodong Ji, Hailin Zhang, Fangcheng Fu, Bin Cui
2024	J	`jnl`	A Unified Framework for Mining Batch and Periodic Batch in Data Streams. IEEE Trans. Knowl. Data Eng. Zirui Liu, Xiangyuan Wang, Yuhan Wu, Tong Yang, Kaicheng Yang, Hailin Zhang, Yaofeng Tu, Bin Cui
2024	J	`jnl`	CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models. Proc. ACM Manag. Data Hailin Zhang, Zirui Liu, Boxuan Chen, Yikai Zhao, Tong Zhao, Tong Yang, Bin Cui
2024	J	`jnl`	Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs. CoRR Pinxue Zhao, Hailin Zhang, Fangcheng Fu, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui
2024	A*	`conf`	Enabling Parallelism Hot Switching for Efficient Training of Large Language Models. SOSP Hao Ge, Fangcheng Fu, Haoyang Li, Xuanyu Wang, Sheng Lin, Yujie Wang, Xiaonan Nie, Hailin Zhang, Xupeng Miao, Bin Cui
2024	J	`jnl`	Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization. CoRR Haoyang Li, Fangcheng Fu, Hao Ge, Sheng Lin, Xuanyu Wang, Jiawen Niu, Yujie Wang, Hailin Zhang, Xiaonan Nie, Bin Cui
2024	J	`jnl`	PQCache: Product Quantization-based KVCache for Long Context LLM Inference. CoRR Hailin Zhang, Xiaodong Ji, Yilin Chen, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Weipeng Chen, Bin Cui
2024	J	`jnl`	Retrieval-Augmented Generation for AI-Generated Content: A Survey. CoRR Penghao Zhao, Hailin Zhang, Qinhan Yu, Zhengren Wang, Yunteng Geng, Fangcheng Fu, Ling Yang, Wentao Zhang, Bin Cui
2024	A*	`conf`	Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling. NeurIPS Shuaipeng Li, Penghao Zhao, Hailin Zhang, Xingwu Sun, Hao Wu, Dian Jiao, Weiyan Wang, Chengjun Liu, Zheng Fang, Jinbao Xue, Yangyu Tao, Bin Cui, Di Wang
2024	J	`jnl`	Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling. CoRR Shuaipeng Li, Penghao Zhao, Hailin Zhang, Xingwu Sun, Hao Wu, Dian Jiao, Weiyan Wang, Chengjun Liu, Zheng Fang, Jinbao Xue, Yangyu Tao, Bin Cui, Di Wang
2023	J	`jnl`	CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models. CoRR Hailin Zhang, Zirui Liu, Boxuan Chen, Yikai Zhao, Tong Zhao, Tong Yang, Bin Cui
2023	J	`jnl`	Experimental Analysis of Large-scale Learnable Vector Storage Compression. CoRR Hailin Zhang, Penghao Zhao, Xupeng Miao, Yingxia Shao, Zirui Liu, Tong Yang, Bin Cui
2023	J	`jnl`	Experimental Analysis of Large-scale Learnable Vector Storage Compression. Proc. VLDB Endow. Hailin Zhang, Penghao Zhao, Xupeng Miao, Yingxia Shao, Zirui Liu, Tong Yang, Bin Cui
2023	J	`jnl`	Hetu: a highly efficient automatic parallel distributed deep learning system. Sci. China Inf. Sci. Xupeng Miao, Xiaonan Nie, Hailin Zhang, Tong Zhao, Bin Cui
2023	A*	`conf`	Model-enhanced Vector Index. NeurIPS Hailin Zhang, Yujing Wang, Qi Chen, Ruiheng Chang, Ting Zhang, Ziming Miao, Yingyan Hou, Yang Ding, Xupeng Miao, Haonan Wang, Bochen Pang, Yuefeng Zhan, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Xing Xie, Mao Yang, Bin Cui
2023	J	`jnl`	Model-enhanced Vector Index. CoRR Hailin Zhang, Yujing Wang, Qi Chen, Ruiheng Chang, Ting Zhang, Ziming Miao, Yingyan Hou, Yang Ding, Xupeng Miao, Haonan Wang, Bochen Pang, Yuefeng Zhan, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Xing Xie, Mao Yang, Bin Cui
2022	J	`jnl`	Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism. CoRR Xupeng Miao, Yujie Wang, Youhe Jiang, Chunan Shi, Xiaonan Nie, Hailin Zhang, Bin Cui
2022	J	`jnl`	Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism. Proc. VLDB Endow. Xupeng Miao, Yujie Wang, Youhe Jiang, Chunan Shi, Xiaonan Nie, Hailin Zhang, Bin Cui
2022	—	`conf`	HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training. SIGMOD Conference Xupeng Miao, Yining Shi, Hailin Zhang, Xin Zhang, Xiaonan Nie, Zhi Yang, Bin Cui
2021	J	`jnl`	HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework. CoRR Xupeng Miao, Hailin Zhang, Yining Shi, Xiaonan Nie, Zhi Yang, Yangyu Tao, Bin Cui
2021	J	`jnl`	HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework. Proc. VLDB Endow. Xupeng Miao, Hailin Zhang, Yining Shi, Xiaonan Nie, Zhi Yang, Yangyu Tao, Bin Cui