Wei Jin

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 67

Top Topics

Graph Representation

Graph Structures

Top Venues

Publications

Hongzhi Wen, Wenzhuo Tang, Xinnan Dai, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang
CellPLM: Pre-training of Cell Language Model Beyond Single Cells. ICLR (2024)
Yi Nian, Yurui Chang, Wei Jin, Lu Lin
Globally Interpretable Graph Learning via Distribution Matching. WWW (2024)
Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective. KDD (2024)
Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
A Review of Graph Neural Networks in Epidemic Modeling. CoRR (2024)
Dylan Molho, Jiayuan Ding, Wenzhuo Tang, Zhaoheng Li, Hongzhi Wen, Yixin Wang, Julian Venegas, Wei Jin, Renming Liu, Runze Su, Patrick Danaher, Robert Yang, Yu Leo Lei, Yuying Xie, Jiliang Tang
Deep Learning in Single-cell Analysis. ACM Trans. Intell. Syst. Technol. 15 (3) (2024)
Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu
A Pure Transformer Pretraining Framework on Text-attributed Graphs. CoRR (2024)
Kai Guo, Zewen Liu, Zhikai Chen, Hongzhi Wen, Wei Jin, Jiliang Tang, Yi Chang
Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness. CoRR (2024)
Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
Label-free Node Classification on Graphs with Large Language Models (LLMs). ICLR (2024)
Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. CoRR (2024)
Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective. CoRR (2024)
Juanhui Li, Haoyu Han, Zhikai Chen, Harry Shomer, Wei Jin, Amin Javari, Jiliang Tang
Enhancing ID and Text Fusion via Alternative Training in Session-based Recommendation. CoRR (2024)
Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
A Review of Graph Neural Networks in Epidemic Modeling. KDD (2024)
Wei Jin, Haohan Wang, Daochen Zha, Qiaoyu Tan, Yao Ma, Sharon Li, Su-In Lee
DCAI: Data-centric Artificial Intelligence. WWW (Companion Volume) (2024)
Ran Xu, Hejie Cui, Yue Yu, Xuan Kan, Wenqi Shi, Yuchen Zhuang, May Dongmei Wang, Wei Jin, Joyce Ho, Carl Yang
Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models. ACL (Findings) (2024)
Mohammad Hashemi, Shengbo Gong, Juntong Ni, Wenqi Fan, B. Aditya Prakash, Wei Jin
A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation. CoRR (2024)
Shengbo Gong, Juntong Ni, Noveen Sachdeva, Carl Yang, Wei Jin
GC-Bench: A Benchmark Framework for Graph Condensation with New Insights. CoRR (2024)
Zewen Liu, Yunxiao Li, Mingyang Wei, Guancheng Wan, Max S. Y. Lau, Wei Jin
EpiLearn: A Python Library for Machine Learning in Epidemic Modeling. CoRR (2024)
Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang
Toward Degree Bias in Embedding-Based Knowledge Graph Completion. CoRR (2023)
Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs. CoRR (2023)
Hua Liu, Haoyu Han, Wei Jin, Xiaorui Liu, Hui Liu
Enhancing Graph Representations Learning with Decorrelated Propagation. KDD (2023)
Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
Label-free Node Classification on Graphs with Large Language Models (LLMS). CoRR (2023)
Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang
Single-Cell Multimodal Prediction via Transformers. CoRR (2023)
Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang
Single-Cell Multimodal Prediction via Transformers. CIKM (2023)
Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang
Exploring the Potential of Large Language Models (LLMs)in Learning on Graphs. SIGKDD Explor. 25 (2) (2023)
Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. CoRR (2023)
Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. NeurIPS (2023)
Harry Shomer, Wei Jin, Juanhui Li, Yao Ma, Hui Liu
Learning Representations for Hyper-Relational Knowledge Graphs. ASONAM (2023)
Kaiqi Yang, Haoyu Han, Wei Jin, Hui Liu
Augment with Care: Enhancing Graph Contrastive Learning with Selective Spectrum Perturbation. CoRR (2023)
Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah
Empowering Graph Representation Learning with Test-Time Graph Transformation. ICLR (2023)
Yiqi Wang, Yao Ma, Wei Jin, Chaozhuo Li, Charu Aggarwal, Jiliang Tang
Customized Graph Nerual Networks. IEEE Data Eng. Bull. 46 (2) (2023)
Tong Zhao, Wei Jin, Yozen Liu, Yingheng Wang, Gang Liu, Stephan Günnemann, Neil Shah, Meng Jiang
Graph Data Augmentation for Graph Machine Learning: A Survey. IEEE Data Eng. Bull. 46 (2) (2023)
Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal
Jointly Attacking Graph Neural Network and its Explanations. ICDE (2023)
Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NeurIPS (2023)
Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. CoRR (2022)
Yiqi Wang, Chaozhuo Li, Wei Jin, Rui Li, Jianan Zhao, Jiliang Tang, Xing Xie
Test-Time Training for Graph Neural Networks. CoRR (2022)
Enyan Dai, Wei Jin, Hui Liu, Suhang Wang
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. CoRR (2022)
Hongzhi Wen, Jiayuan Ding, Wei Jin, Yiqi Wang, Yuying Xie, Jiliang Tang
Graph Neural Networks for Multimodal Single-Cell Data Integration. KDD (2022)
Yiqi Wang, Chaozhuo Li, Mingzheng Li, Wei Jin, Yuming Liu, Hao Sun, Xing Xie, Jiliang Tang
Localized Graph Collaborative Filtering. SDM (2022)
Hongzhi Wen, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang
Graph Neural Networks for Multimodal Single-Cell Data Integration. CoRR (2022)
Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bin Ying
Condensing Graphs via One-Step Gradient Matching. CoRR (2022)
Enyan Dai, Wei Jin, Hui Liu, Suhang Wang
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. WSDM (2022)
Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li
Graph Trend Filtering Networks for Recommendation. SIGIR (2022)
Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah
Graph Condensation for Graph Neural Networks. CoRR (2021)
Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang
Elastic Graph Neural Networks. ICML (2021)
Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang
Node Similarity Preserving Graph Convolutional Networks. WSDM (2021)
Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li
Graph Trend Networks for Recommendations. CoRR (2021)
Wei Jin
Graph Mining with Graph Neural Networks. WSDM (2021)
Yaxin Li, Wei Jin, Han Xu, Jiliang Tang
DeepRobust: a Platform for Adversarial Attacks and Defenses. AAAI (2021)
Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang
Elastic Graph Neural Networks. CoRR (2021)
Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu
Graph Representation Learning: Foundations, Methods, Applications and Systems. KDD (2021)
Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang
Graph Feature Gating Networks. CIKM (2021)
Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification. CoRR (2021)
Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. CoRR (2021)
Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification. ACL/IJCNLP (Findings) (2021)
Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang
Graph Feature Gating Networks. CoRR (2021)
Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
Automated Self-Supervised Learning for Graphs. CoRR (2021)
Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang
Graph Neural Networks with Adaptive Residual. NeurIPS (2021)
Wenqi Fan, Wei Jin, Xiaorui Liu, Han Xu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal
Jointly Attacking Graph Neural Network and its Explanations. CoRR (2021)
Yaxin Li, Wei Jin, Han Xu, Jiliang Tang
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses. CoRR (2020)
Xiaoyang Wang, Yao Ma, Yiqi Wang, Wei Jin, Xin Wang, Jiliang Tang, Caiyan Jia, Jian Yu
Traffic Flow Prediction via Spatial Temporal Graph Neural Network. WWW (2020)
Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang
Graph Structure Learning for Robust Graph Neural Networks. CoRR (2020)
Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Jiliang Tang
Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study. CoRR (2020)
Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang
Node Similarity Preserving Graph Convolutional Networks. CoRR (2020)
Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Shuiwang Ji, Charu Aggarwal, Jiliang Tang
Adversarial Attacks and Defenses on Graphs. SIGKDD Explor. 22 (2) (2020)
Han Xu, Yaxin Li, Wei Jin, Jiliang Tang
Adversarial Attacks and Defenses: Frontiers, Advances and Practice. KDD (2020)
Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang
Graph Structure Learning for Robust Graph Neural Networks. KDD (2020)
Wei Jin, Tyler Derr, Haochen Liu, Yiqi Wang, Suhang Wang, Zitao Liu, Jiliang Tang
Self-supervised Learning on Graphs: Deep Insights and New Direction. CoRR (2020)