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ORCIDYingli Zhou
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2020 – today
- 2025
[j10]Yingli Zhou, Luocheng Liang, Yixiang Fang:
Efficient and Scalable Directed Densest Subgraph Discovery. Proc. ACM Manag. Data 3(6): 1-27 (2025)- [j9]Qiuyang Mang, Jingbang Chen, Hangrui Zhou, Yu Gao, Yingli Zhou, Qingyu Shi, Richard Peng, Yixiang Fang, Chenhao Ma:
Efficient Historical Butterfly Counting in Large Temporal Bipartite Networks via Graph Structure-aware Index. Proc. VLDB Endow. 18(6): 1607-1620 (2025) - [j8]Yingli Zhou, Qingshuo Guo, Yixiang Fang:
Efficient 푘-Clique Densest Subgraph Discovery: Towards Bridging Practice and Theory. Proc. VLDB Endow. 18(10): 3490-3503 (2025) - [j7]Fangyuan Zhang, Mengqi Wu, Chunlei Xu, Yunong Bao, Jiyu Qiao, Yingli Zhou, Hua Fan, Caihua Yin, Wenchao Zhou, Feifei Li:
Streaming View: An Efficient Data Processing Engine for Modern Real-time Data Warehouse of Alibaba Cloud. Proc. VLDB Endow. 18(12): 5153-5165 (2025) - [c2]Yue Zhang
, Yankai Chen, Yingli Zhou, Yucan Guo, Xiaolin Han, Chenhao Ma:
UTCS: Effective Unsupervised Temporal Community Search with Pre-training of Temporal Dynamics and Subgraph Knowledge. SIGIR 2025: 2647-2651 - [i9]Shu Wang, Yixiang Fang, Yingli Zhou, Xilin Liu, Yuchi Ma:
ArchRAG: Attributed Community-based Hierarchical Retrieval-Augmented Generation. CoRR abs/2502.09891 (2025) - [i8]Yingli Zhou, Yaodong Su, Youran Sun, Shu Wang, Taotao Wang, Runyuan He, Yongwei Zhang, Sicong Liang, Xilin Liu, Yuchi Ma, Yixiang Fang:
In-depth Analysis of Graph-based RAG in a Unified Framework. CoRR abs/2503.04338 (2025) - [i7]Jingbang Chen, Weinuo Li, Yingli Zhou, Hangrui Zhou, Qiuyang Mang, Can Wang, Yixiang Fang, Chenhao Ma:
Scalable Approximate Biclique Counting over Large Bipartite Graphs. CoRR abs/2505.10471 (2025) - [i6]Yue Zhang, Yankai Chen, Yingli Zhou, Yucan Guo, Xiaolin Han, Chenhao Ma:
UTCS: Effective Unsupervised Temporal Community Search with Pre-training of Temporal Dynamics and Subgraph Knowledge. CoRR abs/2506.02784 (2025) - [i5]Fangyuan Zhang, Zhengjun Huang, Yingli Zhou, Qintian Guo, Zhixun Li, Wensheng Luo, Di Jiang, Yixiang Fang, Xiaofang Zhou:
EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora. CoRR abs/2506.20963 (2025) - [i4]Yaodong Su, Yixiang Fang, Yingli Zhou, Quanqing Xu, Chuanhui Yang:
CUE-RAG: Towards Accurate and Cost-Efficient Graph-Based RAG via Multi-Partite Graph and Query-Driven Iterative Retrieval. CoRR abs/2507.08445 (2025) - [i3]Zhengjun Huang, Zhoujin Tian, Qintian Guo, Fangyuan Zhang, Yingli Zhou, Di Jiang, Xiaofang Zhou:
LiCoMemory: Lightweight and Cognitive Agentic Memory for Efficient Long-Term Reasoning. CoRR abs/2511.01448 (2025) - 2024
- [j6]Yingli Zhou, Qingshuo Guo, Yixiang Fang, Chenhao Ma:
A Counting-based Approach for Efficient k-Clique Densest Subgraph Discovery. Proc. ACM Manag. Data 2(3): 119 (2024) - [j5]Wensheng Luo, Yixiang Fang, Chunxu Lin, Yingli Zhou:
Efficient Parallel D-core Decomposition at Scale. Proc. VLDB Endow. 17(10): 2654-2667 (2024) - [j4]Yingli Zhou, Yixiang Fang, Chenhao Ma, Tianci Hou, Xin Huang:
Efficient Maximal Motif-Clique Enumeration over Large Heterogeneous Information Networks. Proc. VLDB Endow. 17(11): 2946-2959 (2024) - [j3]Yingli Zhou, Qingshuo Guo, Yi Yang, Yixiang Fang, Chenhao Ma, Laks V. S. Lakshmanan:
In-depth Analysis of Densest Subgraph Discovery in a Unified Framework. Proc. VLDB Endow. 18(4): 1131-1144 (2024) - [c1]Yinzhao Yan, Yicong Huang, Yingli Zhou, Haoran Ding:
Reproducibility Report for ACM SIGMOD 2024 Paper: 'Proving Query Equivalence Using Linear Integer Arithmetic'. SIGMOD/PODS 2024: 55-56 - [i2]Qiuyang Mang, Jingbang Chen, Hangrui Zhou, Yu Gao, Yingli Zhou, Richard Peng, Yixiang Fang, Chenhao Ma:
Efficient Historical Butterfly Counting in Large Temporal Bipartite Networks via Graph Structure-aware Index. CoRR abs/2406.00344 (2024) - [i1]Yingli Zhou, Qingshuo Guo, Yi Yang, Yixiang Fang, Chenhao Ma, Laks V. S. Lakshmanan:
In-depth Analysis of Densest Subgraph Discovery in a Unified Framework. CoRR abs/2406.04738 (2024) - 2023
- [j2]Yingli Zhou, Yixiang Fang, Wensheng Luo, Yunming Ye:
Influential Community Search over Large Heterogeneous Information Networks. Proc. VLDB Endow. 16(8): 2047-2060 (2023) - 2022
- [j1]Chunshan Li, Yingli Zhou, Guoqing Chao, Dianhui Chu:
Understanding users' requirements precisely: a double Bi-LSTM-CRF joint model for detecting user's intentions and slot tags. Neural Comput. Appl. 34(16): 13639-13648 (2022)
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