Context-Aware Session-Based Recommendation with Graph Neural Networks. - Zhihui Zhang; Jianxiang Yu 001; Xiang Li 067 (ICKG, 2023)

Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Weighted Negative Samples. - Jianxiang Yu 001; Xiang Li 067 (SDM, 2023)

Empower Text-Attributed Graphs Learning with Large Language Models (LLMs). - Jianxiang Yu 001; Yuxiang Ren; Chenghua Gong; Jiaqi Tan 006; Xiang Li 067; Xuecang Zhang (CoRR, 2023)

Prompt Tuning for Multi-View Graph Contrastive Learning. - Chenghua Gong; Xiang Li 067; Jianxiang Yu 001; Cheng Yao; Jiaqi Tan 006; Chengcheng Yu; Dawei Yin (CoRR, 2023)

Resist Label Noise with PGM for Graph Neural Networks. - Qingqing Ge; Jianxiang Yu 001; Zeyuan Zhao; Xiang Li 067 (CoRR, 2023)

Self-supervised Heterogeneous Graph Variational Autoencoders. - Yige Zhao; Jianxiang Yu 001; Yao Cheng; Chengcheng Yu; Yiding Liu; Xiang Li 067; Shuaiqiang Wang (CoRR, 2023)

Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis. - Jianxiang Yu 001; Zichen Ding 002; Jiaqi Tan 006; Kangyang Luo; Zhenmin Weng; Chenghua Gong; Long Zeng 004; Renjing Cui; Chengcheng Han 004; Qiushi Sun; Zhiyong Wu 003; Yunshi Lan; et al. (EMNLP (Findings), 2024)

Self-pro: A Self-prompt and Tuning Framework for Graph Neural Networks. - Chenghua Gong; Xiang Li 067; Jianxiang Yu 001; Yao Cheng; Jiaqi Tan 006; Chengcheng Yu (ECML/PKDD (2), 2024)

Towards Learning from Graphs with Heterophily: Progress and Future. - Chenghua Gong; Yao Cheng; Jianxiang Yu 001; Can Xu; Caihua Shan; Siqiang Luo; Xiang Li 067 (CoRR, 2024)

Improving Graph Out-of-distribution Generalization on Real-world Data. - Can Xu; Yao Cheng; Jianxiang Yu 001; Haosen Wang; Jingsong Lv; Xiang Li 067 (CoRR, 2024)

Boosting Graph Foundation Model from Structural Perspective. - Yao Cheng; Yige Zhao; Jianxiang Yu 001; Xiang Li 067 (CoRR, 2024)

Can Large Language Models Act as Ensembler for Multi-GNNs? - Hanqi Duan; Yao Cheng; Jianxiang Yu 001; Xiang Li 067 (CoRR, 2024)

SEAGraph: Unveiling the Whole Story of Paper Review Comments. - Jianxiang Yu 001; Jiaqi Tan 006; Zichen Ding 002; Jiapeng Zhu 002; Jiahao Li; Yao Cheng; Qier Cui; Yunshi Lan; Xiang Li 067 (CoRR, 2024)

Heterogeneous Graph Contrastive Learning With Meta-Path Contexts and Adaptively Weighted Negative Samples. - Jianxiang Yu 001; Qingqing Ge; Xiang Li 067; Aoying Zhou (IEEE Trans. Knowl. Data Eng., 2024)

Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphs. - Jianxiang Yu 001; Yuxiang Ren; Chenghua Gong; Jiaqi Tan 006; Xiang Li 067; Xuecang Zhang (AAAI, 2025)

RELIEF: Reinforcement Learning Empowered Graph Feature Prompt Tuning. - Jiapeng Zhu 002; Zichen Ding 002; Jianxiang Yu 001; Jiaqi Tan 006; Xiang Li 067; Weining Qian (KDD (1), 2025)

Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributes. - Yige Zhao; Jianxiang Yu 001; Yao Cheng; Chengcheng Yu; Yiding Liu; Xiang Li 067; Shuaiqiang Wang (KDD (1), 2025)

Hierarchical Vector Quantized Graph Autoencoder with Annealing-Based Code Selection. - Long Zeng 004; Jianxiang Yu 001; Jiapeng Zhu 002; Qingsong Zhong; Xiang Li 067 (WWW, 2025)

Relation-Aware Graph Foundation Model. - Jianxiang Yu 001; Jiapeng Zhu 002; Hao Qian; Ziqi Liu; Zhiqiang Zhang; Xiang Li 067 (CoRR, 2025)

Breaking the Cloak! Unveiling Chinese Cloaked Toxicity with Homophone Graph and Toxic Lexicon. - Xuchen Ma; Jianxiang Yu 001; Wenming Shao; Bo Pang; Xiang Li 067 (CoRR, 2025)