Kai Guo

27 papers A* 5Journal 20Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Attn-GS: Attention-Guided Context Compression for Efficient Personalized LLMs.
CoRR
Shenglai Zeng, Tianqi Zheng, Chuan Tian, Dante Everaert, Yau-Shian Wang, Yupin Huang, Michael J. Morais, Rohit Patki, Jinjin Tian, Xinnan Dai, Kai Guo, Monica Xiao Cheng, Hui Liu
2026 J jnl
Fix Before Search: Benchmarking Agentic Query Visual Pre-processing in Multimodal Retrieval-augmented Generation.
CoRR
Jiankun Zhang, Shenglai Zeng, Kai Guo, Xinnan Dai, Hui Liu, Jiliang Tang, Yi Chang
2026 A* conf
Reasoning by Exploration: A Unified Approach to Retrieval and Generation over Graphs.
WWW
Haoyu Han, Kai Guo, Harry Shomer, Yu Wang, Yucheng Chu, Hang Li, Li Ma, Jiliang Tang
2025 J jnl
Aligning large language models and geometric deep models for protein representation.
Patterns
Dong Shu, Bingbing Duan, Kai Guo, Kaixiong Zhou, Jiliang Tang, Mengnan Du
2025 J jnl
Beyond Static Retrieval: Opportunities and Pitfalls of Iterative Retrieval in GraphRAG.
CoRR
Kai Guo, Xinnan Dai, Shenglai Zeng, Harry Shomer, Haoyu Han, Yu Wang, Jiliang Tang
2025 A* conf
Empowering GraphRAG with Knowledge Filtering and Integration.
EMNLP
Kai Guo, Harry Shomer, Shenglai Zeng, Haoyu Han, Yu Wang, Jiliang Tang
2025 J jnl
Empowering GraphRAG with Knowledge Filtering and Integration.
CoRR
Kai Guo, Harry Shomer, Shenglai Zeng, Haoyu Han, Yu Wang, Jiliang Tang
2025 J jnl
From Sequence to Structure: Uncovering Substructure Reasoning in Transformers.
CoRR
Xinnan Dai, Kai Yang, Jay Revolinsky, Kai Guo, Aoran Wang, Bohang Zhang, Jiliang Tang
2025 J jnl
GraphGhost: Tracing Structures Behind Large Language Models.
CoRR
Xinnan Dai, Kai Guo, Chung-Hsiang Lo, Shenglai Zeng, Jiayuan Ding, Dongsheng Luo, Subhabrata Mukherjee, Jiliang Tang
2025 J jnl
RAG vs. GraphRAG: A Systematic Evaluation and Key Insights.
CoRR
Haoyu Han, Harry Shomer, Yu Wang, Yongjia Lei, Kai Guo, Zhigang Hua, Bo Long, Hui Liu, Jiliang Tang
2025 J jnl
Reasoning by Exploration: A Unified Approach to Retrieval and Generation over Graphs.
CoRR
Haoyu Han, Kai Guo, Harry Shomer, Yu Wang, Yucheng Chu, Hang Li, Li Ma, Jiliang Tang
2025 J jnl
Retrieval-Augmented Generation with Graphs (GraphRAG).
CoRR
Haoyu Han, Yu Wang, Harry Shomer, Kai Guo, Jiayuan Ding, Yongjia Lei, Mahantesh Halappanavar, Ryan A. Rossi, Subhabrata Mukherjee, Xianfeng Tang, Qi He, Zhigang Hua, Bo Long, Tong Zhao, Neil Shah, Amin Javari, Yinglong Xia, Jiliang Tang
2025 — conf
Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach.
ACL (1)
Shenglai Zeng, Pengfei He, Kai Guo, Tianqi Zheng, Hanqing Lu, Yue Xing, Hui Liu
2025 J jnl
Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach.
CoRR
Shenglai Zeng, Pengfei He, Kai Guo, Tianqi Zheng, Hanqing Lu, Yue Xing, Hui Liu
2025 J jnl
Uncovering Graph Reasoning in Decoder-only Transformers with Circuit Tracing.
CoRR
Xinnan Dai, Chung-Hsiang Lo, Kai Guo, Shenglai Zeng, Dongsheng Luo, Jiliang Tang
2024 J jnl
Breaking the curse of dimensional collapse in graph contrastive learning: A whitening perspective.
Inf. Sci.
Yang Tao, Kai Guo, Yizhen Zheng, Shirui Pan, Xiaofeng Cao, Yi Chang
2024 J jnl
Exploring the Alignment Landscape: LLMs and Geometric Deep Models in Protein Representation.
CoRR
Dong Shu, Bingbing Duan, Kai Guo, Kaixiong Zhou, Jiliang Tang, Mengnan Du
2024 A* conf
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective.
KDD
Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang
2024 J jnl
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective.
CoRR
Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang
2024 J jnl
Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness.
CoRR
Kai Guo, Zewen Liu, Zhikai Chen, Hongzhi Wen, Wei Jin, Jiliang Tang, Yi Chang
2023 A* conf
Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships.
ICML
Yaming Guo, Kai Guo, Xiaofeng Cao, Tieru Wu, Yi Chang
2023 J jnl
Taming over-smoothing representation on heterophilic graphs.
Inf. Sci.
Kai Guo, Xiaofeng Cao, Zhining Liu, Yi Chang
2022 A* conf
Orthogonal Graph Neural Networks.
AAAI
Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang
2021 J jnl
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks.
CoRR
Haotian Xue, Kaixiong Zhou, Tianlong Chen, Kai Guo, Xia Hu, Yi Chang, Xin Wang
2021 J jnl
IMBENS: Ensemble Class-imbalanced Learning in Python.
CoRR
Zhining Liu, Zhepei Wei, Erxin Yu, Qiang Huang, Kai Guo, Boyang Yu, Zhaonian Cai, Hangting Ye, Wei Cao, Jiang Bian, Pengfei Wei, Jing Jiang, Yi Chang
2021 J jnl
Orthogonal Graph Neural Networks.
CoRR
Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang
2018 — conf
Cloud-ocean computing: a new scheme of marine data processing.
WUWNet
Jun Liu, Kai Guo, Jun-Hong Cui