About

Longlon Lin is an Associate Professor at Southwest University. He received a Ph.D. from Huazhong University of Science and Technology (HUST), China, in 2022, advised by Prof. Pingpeng Yuan and Prof. Dongxiao Yu. Besides, from 2018 to now, his co-supervisor is Prof. Rong-Hua Li from Beijing Institute of Technology. His work has been published in several CCF-A conferences and journals, including TKDE, KDD, AAAI, SIGMOD, VLDB, ICDE, ASPLOS, and DAC.

Research Interests

LLM-based Text Attribute Graph Analysis、Graph Machine Learning、Graph Clustering.

[招生信息] : 每年计划招3-5名硕士，研究:

LLM-based Text Attribute Graph Analysis: 主要研究Graph Retrieval Augmented Generation (RAG)如何提升LLM的性能

Graph Machine Learning: 主要关注可扩展性、时序性、鲁棒性、图增强. 可扩展性是如何保质地快速学习十亿级别的图. 鲁棒性和图增强有很多重叠，他们都是data-centric graph learning, 都是对原始图做改变，以防御攻击或者让学习质量更好.

AI-empowered Graph Clustering：社区挖掘目前分为基于规则(Rule-based)的和基于学习的(Learning-based). 我们课题组关注的是如何将两种融合以在质量和效率上达到trade-off，以及如何利用LLM辅助社区的挖掘.

欢迎保研或者考研的学生给我发email (longlonglin@swu.edu.cn). 同时长期招收大一/大二本科生,但有如下要求：1.以培养科研方法论为目的(能发CCF B/中科院二区为佳); 2.由我亲自指导并给出具体的研究问题和算法框架。细节和实验由你独立完成但随时随地可讨论. 3.科研的周期较长，不做短平快的工作. 优秀的本硕学生可推荐到阿里，华为等大厂实习或国内外top高校继续深造。

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Selected Publications

A full list of publications can be found at Google Scholar. Please see my research projects/code on GitHub.

2026:

• [25] Longlong Lin, Zeli Wang, Rong-Hua Li, Qiyu Liu, Hongchao Qin, Jin Zhao. Provable Higher-order Graph Clustering: the Power of Peeling-based Approaches. TKDE, 2026 ( CCF-A期刊 )
• [24] Junjie Zhou, Meihao Liao, Rong-Hua Li, Longlong Lin, Guoren Wang. One Index for All: Towards Efficient Personalized PageRank Computation for Every Damping Factor. SIGMOD, 2026 ( CCF-A会议 )

2025:

• [23] Yalong Zhang, Rong-Hua Li, Longlong Lin, Qi Zhang, Guoren Wang. Integral Densest Subgraph Search on Directed Graphs. SIGMOD, 2025 ( CCF-A会议 )
• [22] Hongchao Qin, Guang Zeng, Rong-Hua Li, Longlong Lin, Ye Yuan, Guoren Wang. Truss Decomposition in Hypergraphs. VLDB, 2025 ( CCF-A会议 )
• [21] Qiyu Liu, Siyuan Han, Yanlin Qi, Jingshu Peng, Jin Li, Longlong Lin, Lei Chen. Why Are Learned Indexes So Effective but Sometimes Ineffective? VLDB, 2025 ( CCF-A会议 )
• [20] Xiaoyu Leng, Guang Zeng, Hongchao Qin, Longlong Lin, Rong-Hua Li, On Temporal-Constraint Subgraph Matching. ICDE, 2025 ( CCF-A会议 )
• [19] Jin Zhao, Qian Wang, Ligang He, Yu Zhang, Sheng Di, Bingsheng He, Xinlei Wang, Hui Yu, Hao Qi, Longlong Lin, Linchen Yu, Xiaofei Liao, Hai Jin. TempGraph: An Efficient Chain-driven Temporal Graph Computing Framework on the GPU. ASPLOS, 2025 ( CCF-A会议 ).
• [18] Jin Zhao, Yu Zhang, Jun Huang, Weihang Yin, Hui Yu, Hao Qi, Zixiao Wang, Longlong Lin, Xiaofei Liao and Hai Jin. A Data-Centric Hardware Accelerator for Efficient Adaptive Radix Tree. DAC, 2025 ( CCF-A会议 )
• [17] Longlong Lin, Xin Luo. Dual Channel Graph Convolutional Networks via Personalized PageRank. IEEE/CAA Journal of Automatica Sinica, 2025 (中科院一区)
• [16] Tao Liu, Longlong Lin, Yunfeng Yu, Xi Ou, Youan Zhang, Zhiqiu Ye, Tao Jia. CoATA: Effective Co-Augmentation of Topology and Attribute for Graph Neural Networks. ICMR, 2025 (CCF-B会议)

2024:

• [15] Longlong Lin, Pingpeng Yuan, Rong-Hua Li, Chunxue Zhu, Hongchao Qin, Hai Jin, Tao Jia. QTCS: Efficient Query-Centered Temporal Community Search. Proceedings of the VLDB Endowment, 2024, 17(6):1187-1199 ( CCF-A会议 )
• [14] Longlong Lin, Tao Jia, Zeli Wang, Jin Zhao, Rong-Hua Li. PSMC: Provable and Scalable Algorithms for Motif Conductance Based Graph Clustering. KDD，2024 ( CCF-A会议, Oral )
• [13] Yuchen Meng, Rong-Hua Li, Longlong Lin, Xunkai Li, Guoren Wang. Topology-preserving Graph Coarsening: An Elementary Collapse-based Approach. VLDB, 2024 ( CCF-A会议 )
• [12] Xiaowei Ye, Rong-Hua Li, Lei Liang, Zhizhen Liu, Longlong Lin, Guoren Wang. Efficient and Effective Anchored Densest Subgraph Search: A Convex-programming based Approach. KDD, 2024 ( CCF-A会议, Oral )
• [11] Longlong Lin, Yunfeng Yu, Zihao Wang, Zeli Wang, Yuying Zhao, Jin Zhao, Tao Jia. PSNE: Efficient Spectral Sparsification Algorithms for Scaling Network Embedding. CIKM, 2024 (CCF-B会议)
• [10] Yue He, Longlong Lin, Pingpeng Yuan, Rong-Hua Li, Tao Jia, Zeli Wang. CCSS: Towards Conductance-based Community Search with Size Constraints. Expert Systems with Applications, 2024 (中科院1区)
• [9] Yunfeng Yu, Longlong Lin, Qiyu Liu, Zeli Wang, Xi Ou, Tao Jia. GSD-GNN: Generalizable and Scalable Algorithms for Decoupled Graph Neural Networks. ICMR, 2024 (CCF-B会议, Oral)
• [8] Zeli Wang, Tuo Zhang, Shuyin Xia, Longlong Lin, Guoyin Wang. GBRAIN: Combating Textual Label Noise by Granular-ball Robust Training. ICMR, 2024 (CCF-B会议, Oral)
• [7] Zeli Wang, Jian Li, Shuyin Xia, Longlong Lin, Guoyin Wang. Text Adversarial Defense via Granular-Ball Sample Enhancement. ICMR, 2024 (CCF-B会议, Oral)

2023:

• [6] Longlong Lin, Rong-Hua Li, Tao Jia. Scalable and Effective Conductance-based Graph Clustering. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, USA, February 7-14, 2023:4471-4478 ( CCF-A会议, Oral )

2022:

• [5] Longlong Lin, Pingpeng Yuan, Rong-Hua Li, Jifei Wang, Ling Liu, Hai Jin. Mining Stable Quasi-Cliques on Temporal Networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 52(6):3731-3745 (TSMC, 中科院1区)
• [4] Longlong Lin, Pingpeng Yua, Rong-Hua Li, Hai Jin. Mining Diversified Top-r Lasting Cohesive Subgraphs on Temporal Networks. IEEE Transactions on Big Data, 2022, 8(6): 1537-1549 (TBD, 中科院2区)
• [3] Yifei Zhang, Longlong Lin, Pingpeng Yuan, Hai Jin. Significant Engagement Community Search on Temporal Networks. In: Proceedings of Database Systems for Advanced Applications (DASFAA), Virtual Event, April 11–14, 2022:250-258 (CCF-B会议)
• [2] Chunxue Zhu, Longlong Lin, Pingpeng Yuan, Hai Jin. Discovering Cohesive Temporal Subgraphs with Temporal Density Aware Exploration. Journal of Computer Science and Technology, 2022, 37(5):1068-1085 (中科院2区)

2019:

• [1] Pingpeng Yuan, Longlong Lin, Zhijuan Kou, Ling Liu, Hai Jin. Big RDF Data Storage, Computation, and Analysis: A Strawman’s Arguments. In: Proceedings of the International Conference on Distributed Computing Systems (ICDCS), Dallas, TX, USA, July 7-10, 2019:1693-1703 (ICDCS, CCF-B会议)

Work Experience

Beijing Institute of Technology, China, July 2024 - Sep 2024, cooperate with Prof. Rong-Hua Li.

Zhejiang Lab, Hangzhou, China, July 2023 - Sep 2023, cooperate with Prof. Yu Zhang and Prof. Jin Zhao.

Academic Services

(External) Conference Reviewer: VLDB 2024, KDD(2021-2022,2024, 2025 and Award Outstanding Reviewers), NIPS 2025, WWW 2022, AAAI(2022-2025), ICMR (2024-2025), WSDM 2022, CIKM 2020

Invited Journal Reviewer: IEEE-TKDE, IEEE-TC, IEEE-TSUSC, KBS

Publicity Chairs in the 21st IEEE International Conference on Green Computing and Communications