Cloud-ocean computing: a new scheme of marine data processing. - Jun Liu 006; Kai Guo 003; Jun-Hong Cui (WUWNet, 2018)

CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks. - Haotian Xue 001; Kaixiong Zhou; Tianlong Chen 001; Kai Guo 003; Xia Hu 001; Yi Chang 001; Xin Wang 035 (CoRR, 2021)

IMBENS: Ensemble Class-imbalanced Learning in Python. - Zhining Liu 002; Zhepei Wei; Erxin Yu; Qiang Huang; Kai Guo 003; Boyang Yu; Zhaonian Cai; Hangting Ye; Wei Cao 007; Jiang Bian 002; Pengfei Wei 001; Jing Jiang 002; et al. (CoRR, 2021)

Orthogonal Graph Neural Networks. - Kai Guo 003; Kaixiong Zhou; Xia Hu 001; Yu Li 022; Yi Chang 001; Xin Wang 035 (AAAI, 2022)

Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships. - Yaming Guo; Kai Guo 003; Xiaofeng Cao 002; Tieru Wu; Yi Chang 001 (ICML, 2023)

Taming over-smoothing representation on heterophilic graphs. - Kai Guo 003; Xiaofeng Cao 002; Zhining Liu 002; Yi Chang 001 (Inf. Sci., 2023)

Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective. - Kai Guo 003; Hongzhi Wen; Wei Jin 009; Yaming Guo; Jiliang Tang; Yi Chang 001 (KDD, 2024)

Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness. - Kai Guo 003; Zewen Liu 005; Zhikai Chen; Hongzhi Wen; Wei Jin 009; Jiliang Tang; Yi Chang 001 (CoRR, 2024)

Exploring the Alignment Landscape: LLMs and Geometric Deep Models in Protein Representation. - Dong Shu; Bingbing Duan; Kai Guo 003; Kaixiong Zhou; Jiliang Tang; Mengnan Du (CoRR, 2024)

Breaking the curse of dimensional collapse in graph contrastive learning: A whitening perspective. - Yang Tao; Kai Guo 003; Yizhen Zheng; Shirui Pan; Xiaofeng Cao 002; Yi Chang 001 (Inf. Sci., 2024)

Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach. - Shenglai Zeng; Pengfei He; Kai Guo 003; Tianqi Zheng; Hanqing Lu; Yue Xing 002; Hui Liu 031 (ACL (1), 2025)

Aligning large language models and geometric deep models for protein representation. - Dong Shu; Bingbing Duan; Kai Guo 003; Kaixiong Zhou; Jiliang Tang; Mengnan Du (Patterns, 2025)

Retrieval-Augmented Generation with Graphs (GraphRAG). - Haoyu Han 001; Yu Wang 160; Harry Shomer; Kai Guo 003; Jiayuan Ding; Yongjia Lei; Mahantesh Halappanavar; Ryan A. Rossi; Subhabrata Mukherjee; Xianfeng Tang; Qi He 002; Zhigang Hua; et al. (CoRR, 2025)

RAG vs. GraphRAG: A Systematic Evaluation and Key Insights. - Haoyu Han 001; Harry Shomer; Yu Wang 160; Yongjia Lei; Kai Guo 003; Zhigang Hua; Bo Long; Hui Liu 031; Jiliang Tang (CoRR, 2025)

Empowering GraphRAG with Knowledge Filtering and Integration. - Kai Guo 003; Harry Shomer; Shenglai Zeng; Haoyu Han 001; Yu Wang 160; Jiliang Tang (CoRR, 2025)

From Sequence to Structure: Uncovering Substructure Reasoning in Transformers. - Xinnan Dai; Kai Yang; Jay Revolinsky; Kai Guo 003; Aoran Wang; Bohang Zhang; Jiliang Tang (CoRR, 2025)