📝 Publications 
Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphs
Jianxiang Yu, Yuxiang Ren, Chenghua Gong, Jiaqi Tan, Xiang Li, Xuecang Zhang.
- First to leverage LLMs for node generation in graph learning. 🔍
- A plug-and-play, lightweight framework with minimal overhead with minimal overhead. 🚀
Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis 
Jianxiang Yu*, Zichen Ding*, Jiaqi Tan, Kangyang Luo, Zhenmin Weng, Chenghua Gong, Long Zeng, Renjing Cui, Chengcheng Han, Qiushi Sun, Zhiyong Wu, Yunshi Lan, Xiang Li.
- Check demos at Our Website. 🌐
- The model is available at hugging face. 🤗
- An innovative framework for automating peer review. 🌊
Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Adaptively Weighted Negative Samples
Jianxiang Yu, Qingqing Ge, Xiang Li, Aoying Zhou.
- Coarse and fine-grained views for HIN contrastive learning. 🐾
- Gradient-based InfoNCE analysis and weighted contrastive loss design. 🎯
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FCS 2025Boosting Cross-Domain and Cross-Task Generalization for Text-Attributed Graphs from Structural Perspective,
Yao Cheng, Jiapeng Zhu, Yige Zhao, Jianxiang Yu, Xiang Li. -
FCS 2025A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions,
Chenghua Gong, Yao Cheng, Jianxiang Yu, Can Xu, Caihua Shan, Siqiang Luo, Xiang Li -
WWW 2025Hierarchical Vector Quantized Graph Autoencoder with Annealing-Based Code Selection,
Long Zeng, Jianxiang Yu, Jiapeng Zhu, Qingsong Zhong, Xiang Li -
KDD 2025Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributes,
Yige Zhao, Jianxiang Yu, Yao Cheng, Chengcheng Yu, Yiding Liu, Xiang Li, Shuaiqiang Wang. -
KDD 2025RELIEF: Reinforcement Learning Empowered Graph Feature Prompt Tuning,
Jiapeng Zhu, Zichen Ding, Jianxiang Yu, Jiaqi Tan, Xiang Li. -
ECML PKDD 2024Self-Pro: Self-Prompt and Tuning Framework for Graph Neural Networks,
ChengHua Gong, Xiang Li, Jianxiang Yu, Yao Cheng, Jiaqi Tan, Chengcheng Yu.
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SDM 2023Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Weighted Negative Samples,
Jianxiang Yu, Xiang Li. -
ICKG 2023Context-Aware Session-Based Recommendation with Graph Neural Networks,
Zhihui Zhang, Jianxiang Yu, Xiang Li.
More preprints under review will be released soon, and some papers can be found on Google Scholar. 📚✨🔍