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 top conferences and journals including KDD, SIGMOD, VLDB, ICDE, AAAI, DAC, CIKM, ICDCS, and IEEE TSMC.

Research Interests

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

[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 Gernaration (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.

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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.

2025:

• [19] Yalong Zhang, Rong-Hua Li, Longlong Lin, Qi Zhang, Guoren Wang. Integral Densest Subgraph Search on Directed Graphs. SIGMOD, 2025 (CCF-A会议)
• [18] Hongchao Qin, Guang Zeng, Rong-Hua Li, Longlong Lin, Ye Yuan, Guoren Wang. Truss Decomposition in Hypergraphs. VLDB, 2025 (CCF-A会议)
• [17] Xiaoyu Leng, Guang Zeng, Hongchao Qin, Longlong Lin, Rong-Hua Li, On Temporal-Constraint Subgraph Matching. ICDE, 2025 (CCF-A会议)
• [16] 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)

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，二作为指导的研究生)
• [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, 一作为指导的研究生)
• [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, 一作为指导的研究生)
• [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 Dr. Jin Zhao.

Academic Services

(External) Conference Reviewer: VLDB 2024, KDD(2021-2022,2024,2025), WWW 2022, AAAI(2022-2024), WSDM 2022, CIKM 2020

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