Jingzhe Liu

According to our database, Jingzhe Liu authored at least 14 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Understanding Generative Recommendation with Semantic IDs from a Model-scaling View.

Jingzhe Liu, Liam Collins, Jiliang Tang, Tong Zhao, Neil Shah, Clark Mingxuan Ju

CoRR, September, 2025

GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning.

Yu Song, Zhigang Hua, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu

CoRR, September, 2025

A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation.

Yu Song, Zhigang Hua, Harry Shomer, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu

CoRR, August, 2025

Higher-order Structure Boosts Link Prediction on Temporal Graphs.

Jingzhe Liu, Zhigang Hua, Yan Xie, Bingheng Li, Harry Shomer, Yu Song, Kaveh Hassani, Jiliang Tang

CoRR, May, 2025

Unveiling Mode Connectivity in Graph Neural Networks.

Bingheng Li, Zhikai Chen, Haoyu Han, Shenglai Zeng, Jingzhe Liu, Jiliang Tang

CoRR, February, 2025

Unveiling Mode Connectivity in Graph Neural Network.

Bingheng Li, Zhikai Chen, Haoyu Han, Shenglai Zeng, Jingzhe Liu, Jiliang Tang

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

2024

One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs.

Jingzhe Liu, Haitao Mao, Zhikai Chen, Wenqi Fan, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang

CoRR, 2024

Robust Simultaneous Multislice MRI Reconstruction Using Deep Generative Priors.

Shoujin Huang, Guanxiong Luo, Yuwan Wang, Kexin Yang, Lingyan Zhang, Jingzhe Liu, Hua Guo, Min Wang, Mengye Lyu

CoRR, 2024

Neural Scaling Laws on Graphs.

Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang

CoRR, 2024

Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights.

Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

A Pure Transformer Pretraining Framework on Text-Attributed Graphs.

Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu

Proceedings of the Learning on Graphs Conference, 26-29 November 2024, Virtual., 2024

Do Neural Scaling Laws Exist on Graph Self-Supervised Learning?

Qian Ma, Haitao Mao, Jingzhe Liu, Zhehua Zhang, Chunlin Feng, Yu Song, Yihan Shao, Yao Ma

Proceedings of the Learning on Graphs Conference, 26-29 November 2024, Virtual., 2024

Towards Neural Scaling Laws on Graphs.

Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang

Proceedings of the Learning on Graphs Conference, 26-29 November 2024, Virtual., 2024

2022

Penalty Prediction Based on Modulated Hierarchical Attention Coupled with Legal Attribute Recognition.

Jingzhe Liu, Peng Wu

Proceedings of the IEEE International Conference on Big Data, 2022