I am currently a first-year Ph.D. Student at the School of Data Science and Engineering, East China Normal University, under the supervision of Prof. Xiang Li in the PLANING lab.
My research interests include:
- Data mining: graph neural networks, heterogeneous graph mining;
- Large Language Models: applications in scientific research, knowledge editing;
- Combination of GNNs and LLMs: graph foundation models, graph prompt learning.
🎉🎉🎉 Feel free to reach out to me for academic discussions and collaborations!
📝 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 & weighted contrastive loss design. 🎯
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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. 📚✨🔍
📑 Preprint
Relation-Aware Graph Foundation Model
Jianxiang Yu, Jiapeng Zhu, Hao Qian, Ziqi Liu, Zhiqiang Zhang, Xiang Li.
- A relation-aware pre-training framework for graph foundation models. ⚙️
- Robust generalization and effective transferability. 💪
SEAGraph: Unveiling the Whole Story of Paper Review Comments
Jianxiang Yu*, Jiaqi Tan*, Zichen Ding, Jiapeng Zhu, Jiaqi Li, Yao Cheng, Qier Cui, Yunshi Lan, Yao Liu, Xiang Li.
- Constructing Semantic Mind Graphs and Hierarchical Background Graphs to simulate reviewer thinking. 🧠
- Retrieving with GraphRAG to unevil review comments. 📚
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Breaking the Cloak! Unveiling Chinese Cloaked Toxicity with Homophone Graph and Toxic Lexicon,
Xuchen Ma, Jianxiang Yu, Wenming Shao, Bo Pang, Xiang Li. -
Can Large Language Models Act as Ensembler for Multi-GNNs?,
Hanqi Duan, Yao Cheng, Jianxiang Yu, Xiang Li. -
Boosting Cross-Domain and Cross-Task Generalization for Text-Attributed Graphs from Structural Perspective,
Yao Cheng, Jiapeng Zhu, Jianxiang Yu, Xiang Li. -
Improving Graph Out-of-distribution Generalization on Real-world Data,,
Can Xu, Yao Cheng, Jianxiang Yu, Haoran Wang, Jun Lv, Xiang Li. -
Probabilistic Graphical Model for Robust Graph Neural Networks against Noisy Labels,,
Qingqing Ge, Jianxiang Yu, Zeyuan Zhao, Xiang Li.
🌟 Experience
- 2024.11 Attend EMNLP 2024 in Miami, USA.
- 2024.10 Give a talk at EMNLP 2024 pre-presentation event organized by AI TIME.
🎖 Honors and Awards
- 2024.05 Outstanding Graduate, East China Normal University
- 2023.11 Second Prize Enterprise Scholarship, School of Data Science and Engineering, East China Normal University
📖 Educations
- 2024.09 - now Ph.D. candidate, East China Normal University
- 2021.09 - 2024.06 Master, DASE, East China Normal University
- 2017.09 - 2021.06 Undergraduate, Honor College, Hangzhou Dianzi University
💻 Internships
- 2024.06 - 2025.02 Ant Group, Shanghai, China
- 2023.07 - 2023.12 Advance Computing and Storage Lab, 2012 Labs, Huawei Technologies, Shanghai, China
