EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks. - Runlin Lei; Zhen Wang 036; Yaliang Li; Bolin Ding; Zhewei Wei (NeurIPS, 2022)

Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks. - Jie Peng 005; Runlin Lei; Zhewei Wei (CIKM, 2024)

PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters. - Jingyu Chen; Runlin Lei; Zhewei Wei (ICLR, 2024)

Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level. - Runlin Lei; Yuwei Hu; Yuchen Ren 005; Zhewei Wei (NeurIPS, 2024)

Scalable and Accurate Graph Reasoning with LLM-based Multi-Agents. - Yuwei Hu; Runlin Lei; Xinyi Huang; Zhewei Wei; Yongchao Liu (CoRR, 2024)

Dynamic and Textual Graph Generation Via Large-Scale LLM-based Agent Simulation. - Jiarui Ji; Runlin Lei; Jialing Bi; Zhewei Wei; Yankai Lin; Xuchen Pan; Yaliang Li; Bolin Ding (CoRR, 2024)

Learning-based Property Estimation with Polynomials. - Jiajun Li; Runlin Lei; Sibo Wang 001; Zhewei Wei; Bolin Ding (Proc. ACM Manag. Data, 2024)

LLM-Based Multi-Agent Systems are Scalable Graph Generative Models. - Jiarui Ji; Runlin Lei; Jialing Bi; Zhewei Wei; Xu Chen 017; Yankai Lin; Xuchen Pan; Yaliang Li; Bolin Ding (ACL (Findings), 2025)

Exploring the Potential of Large Language Models as Predictors in Dynamic Text-Attributed Graphs. - Runlin Lei; Jiarui Ji; Haipeng Ding 002; Lu Yi 002; Zhewei Wei; Yongchao Liu; Chuntao Hong (CoRR, 2025)

Future Link Prediction Without Memory or Aggregation. - Lu Yi 002; Runlin Lei; Fengran Mo; Yanping Zheng; Zhewei Wei; Yuhang Ye 002 (CoRR, 2025)

GDGB: A Benchmark for Generative Dynamic Text-Attributed Graph Learning. - Jie Peng 005; Jiarui Ji; Runlin Lei; Zhewei Wei; Yongchao Liu; Chuntao Hong (CoRR, 2025)

A survey of estimating number of distinct values. - Jiajun Li; Runlin Lei; Zhewei Wei (Frontiers Comput. Sci., 2025)