Actionable Objective Optimization for Suspicious Behavior Detection on Large Bipartite Graphs. - Tong Zhao 003; Matthew Malir; Meng Jiang 001 (IEEE BigData, 2018)

CTGA: Graph-based Biomedical Literature Search. - Tianwen Jiang; Zhihan Zhang 001; Tong Zhao 003; Bing Qin 001; Ting Liu 001; Nitesh V. Chawla; Meng Jiang 001 (BIBM, 2019)

Multi-Input Multi-Output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text. - Tianwen Jiang; Tong Zhao 003; Bing Qin 001; Ting Liu 001; Nitesh V. Chawla; Meng Jiang 001 (EMNLP/IJCNLP (1), 2019)

The Role of: A Novel Scientific Knowledge Graph Representation and Construction Model. - Tianwen Jiang; Tong Zhao 003; Bing Qin 001; Ting Liu 001; Nitesh V. Chawla; Meng Jiang 001 (KDD, 2019)

Constructing Information-Lossless Biological Knowledge Graphs from Conditional Statements. - Tianwen Jiang; Tong Zhao 003; Bing Qin 001; Ting Liu 001; Nitesh V. Chawla; Meng Jiang 001 (CoRR, 2019)

Error-Bounded Graph Anomaly Loss for GNNs. - Tong Zhao 003; Chuchen Deng; Kaifeng Yu; Tianwen Jiang; Daheng Wang; Meng Jiang 001 (CIKM, 2020)

Identifying Referential Intention with Heterogeneous Contexts. - Wenhao Yu 002; Mengxia Yu; Tong Zhao 003; Meng Jiang 001 (WWW, 2020)

A Probabilistic Model with Commonsense Constraints for Pattern-based Temporal Fact Extraction. - Yang Zhou; Tong Zhao 003; Meng Jiang 001 (CoRR, 2020)

Canonicalizing Open Knowledge Bases with Multi-Layered Meta-Graph Neural Network. - Tianwen Jiang; Tong Zhao 003; Bing Qin 001; Ting Liu 001; Nitesh V. Chawla; Meng Jiang 001 (CoRR, 2020)

Learning Attribute-Structure Co-Evolutions in Dynamic Graphs. - Daheng Wang; Zhihan Zhang 001; Yihong Ma; Tong Zhao 003; Tianwen Jiang; Nitesh V. Chawla; Meng Jiang 001 (CoRR, 2020)

Neural Time-Dependent Partial Differential Equation. - Yihao Hu 003; Tong Zhao 003; Zhiliang Xu; Lizhen Lin (CoRR, 2020)

Federated Dynamic GNN with Secure Aggregation. - Meng Jiang 001; Taeho Jung; Ryan Karl; Tong Zhao 003 (CoRR, 2020)

Early Anomaly Detection by Learning and Forecasting Behavior. - Tong Zhao 003; Bo Ni; Wenhao Yu 002; Meng Jiang 001 (CoRR, 2020)

Data Augmentation for Graph Neural Networks. - Tong Zhao 003; Yozen Liu; Leonardo Neves; Oliver J. Woodford; Meng Jiang 001; Neil Shah (AAAI, 2021)

A Unified View on Graph Neural Networks as Graph Signal Denoising. - Yao Ma 001; Xiaorui Liu; Tong Zhao 003; Yozen Liu; Jiliang Tang; Neil Shah (CIKM, 2021)

Action Sequence Augmentation for Early Graph-based Anomaly Detection. - Tong Zhao 003; Bo Ni; Wenhao Yu 002; Zhichun Guo; Neil Shah; Meng Jiang 001 (CIKM, 2021)

Sentence-Permuted Paragraph Generation. - Wenhao Yu 002; Chenguang Zhu 001; Tong Zhao 003; Zhichun Guo; Meng Jiang 001 (EMNLP (1), 2021)

Dynamic Attributed Graph Prediction with Conditional Normalizing Flows. - Daheng Wang; Tong Zhao 003; Nitesh V. Chawla; Meng Jiang 001 (ICDM, 2021)

Counterfactual Graph Learning for Link Prediction. - Tong Zhao 003; Gang Liu 025; Daheng Wang; Wenhao Yu 002; Meng Jiang 001 (CoRR, 2021)

Biomedical Knowledge Graphs Construction From Conditional Statements. - Tianwen Jiang; Qingkai Zeng 001; Tong Zhao 003; Bing Qin 001; Ting Liu 001; Nitesh V. Chawla; Meng Jiang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts. - Wenhao Yu 002; Chenguang Zhu 001; Lianhui Qin; Zhihan Zhang 001; Tong Zhao 003; Meng Jiang 001 (ACL (Findings), 2022)

Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering. - Mingxuan Ju; Wenhao Yu 002; Tong Zhao 003; Chuxu Zhang; Yanfang Ye 001 (EMNLP (Findings), 2022)

Learning from Counterfactual Links for Link Prediction. - Tong Zhao 003; Gang Liu 025; Daheng Wang; Wenhao Yu 002; Meng Jiang 001 (ICML, 2022)

Graph Rationalization with Environment-based Augmentations. - Gang Liu 025; Tong Zhao 003; Jiaxin Xu; Tengfei Luo; Meng Jiang 001 (KDD, 2022)

Flashlight: Scalable Link Prediction With Effective Decoders. - Yiwei Wang 001; Bryan Hooi; Yozen Liu; Tong Zhao 003; Zhichun Guo; Neil Shah (LoG, 2022)

AutoGDA: Automated Graph Data Augmentation for Node Classification. - Tong Zhao 003; Xianfeng Tang; Danqing Zhang; Haoming Jiang; Nikhil Rao 001; Yiwei Song; Pallav Agrawal; Karthik Subbian; Bing Yin; Meng Jiang 001 (LoG, 2022)

Neural-PDE: a RNN based neural network for solving time dependent PDEs. - Yihao Hu 003; Tong Zhao 003; Shixin Xu; Lizhen Lin; Zhiliang Xu (Commun. Inf. Syst., 2022)

Graph Data Augmentation for Graph Machine Learning: A Survey. - Tong Zhao 003; Gang Liu 025; Stephan Günnemann; Meng Jiang 001 (CoRR, 2022)

Federated Dynamic Graph Neural Networks with Secure Aggregation for Video-based Distributed Surveillance. - Meng Jiang 001; Taeho Jung; Ryan Karl; Tong Zhao 003 (ACM Trans. Intell. Syst. Technol., 2022)

A Synergistic Approach for Graph Anomaly Detection With Pattern Mining and Feature Learning. - Tong Zhao 003; Tianwen Jiang; Neil Shah; Meng Jiang 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Empowering Graph Representation Learning with Test-Time Graph Transformation. - Wei Jin 009; Tong Zhao 003; Jiayuan Ding; Yozen Liu; Jiliang Tang; Neil Shah (ICLR, 2023)

MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization. - Xiaotian Han; Tong Zhao 003; Yozen Liu; Xia Hu 001; Neil Shah (ICLR, 2023)

Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization. - Mingxuan Ju; Tong Zhao 003; Qianlong Wen; Wenhao Yu 002; Neil Shah; Yanfang Ye 001; Chuxu Zhang (ICLR, 2023)

Link Prediction with Non-Contrastive Learning. - William Shiao; Zhichun Guo; Tong Zhao 003; Evangelos E. Papalexakis; Yozen Liu; Neil Shah (ICLR, 2023)

Linkless Link Prediction via Relational Distillation. - Zhichun Guo; William Shiao; Shichang Zhang; Yozen Liu; Nitesh V. Chawla; Neil Shah; Tong Zhao 003 (ICML, 2023)

Semi-Supervised Graph Imbalanced Regression. - Gang Liu 025; Tong Zhao 003; Eric Inae; Tengfei Luo; Meng Jiang 001 (KDD, 2023)

CARL-G: Clustering-Accelerated Representation Learning on Graphs. - William Shiao; Uday Singh Saini; Yozen Liu; Tong Zhao 003; Neil Shah; Evangelos E. Papalexakis (KDD, 2023)

Large-Scale Graph Neural Networks: The Past and New Frontiers. - Rui Xue 006; Haoyu Han 001; Tong Zhao 003; Neil Shah; Jiliang Tang; Xiaorui Liu (KDD, 2023)

GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation. - Mingxuan Ju; Tong Zhao 003; Wenhao Yu 002; Neil Shah; Yanfang Ye 001 (NeurIPS, 2023)

Data-Centric Learning from Unlabeled Graphs with Diffusion Model. - Gang Liu 025; Eric Inae; Tong Zhao 003; Jiaxin Xu; Tengfei Luo; Meng Jiang 001 (NeurIPS, 2023)

Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? - Haitao Mao; Zhikai Chen; Wei Jin 009; Haoyu Han 001; Yao Ma 001; Tong Zhao 003; Neil Shah; Jiliang Tang (NeurIPS, 2023)

Graph Transformers for Large Graphs. - Vijay Prakash Dwivedi; Yozen Liu; Anh Tuan Luu; Xavier Bresson; Neil Shah; Tong Zhao 003 (CoRR, 2023)

Graph Data Augmentation for Graph Machine Learning: A Survey. - Tong Zhao 003; Wei Jin 009; Yozen Liu; Yingheng Wang; Gang Liu 025; Stephan Günnemann; Neil Shah; Meng Jiang 001 (IEEE Data Eng. Bull., 2023)

Modeling Co-Evolution of Attributed and Structural Information in Graph Sequence. - Daheng Wang; Zhihan Zhang 001; Yihong Ma; Tong Zhao 003; Tianwen Jiang; Nitesh V. Chawla; Meng Jiang 001 (IEEE Trans. Knowl. Data Eng., 2023)

Deep Multimodal Complementarity Learning. - Daheng Wang; Tong Zhao 003; Wenhao Yu 002; Nitesh V. Chawla; Meng Jiang 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Learning from Graphs Beyond Message Passing Neural Networks. - Tong Zhao 003; Neil Shah; Elham Ghazizadeh (Tiny Papers @ ICLR, 2024)

A Topological Perspective on Demystifying GNN-Based Link Prediction Performance. - Yu Wang 160; Tong Zhao 003; Yuying Zhao; Yunchao Liu 001; Xueqi Cheng; Neil Shah; Tyler Derr (ICLR, 2024)

Revisiting Link Prediction: a data perspective. - Haitao Mao; Juanhui Li; Harry Shomer; Bingheng Li; Wenqi Fan; Yao Ma 001; Tong Zhao 003; Neil Shah; Jiliang Tang (ICLR, 2024)

LLaGA: Large Language and Graph Assistant. - Runjin Chen; Tong Zhao 003; Ajay Kumar Jaiswal; Neil Shah; Zhangyang Wang (ICML, 2024)

Position: Graph Foundation Models Are Already Here. - Haitao Mao; Zhikai Chen; Wenzhuo Tang; Jianan Zhao 002; Yao Ma 001; Tong Zhao 003; Neil Shah; Mikhail Galkin 001; Jiliang Tang (ICML, 2024)

Towards Neural Scaling Laws on Graphs. - Jingzhe Liu; Haitao Mao; Zhikai Chen; Tong Zhao 003; Neil Shah; Jiliang Tang (LoG, 2024)

How Does Message Passing Improve Collaborative Filtering? - Mingxuan Ju; William Shiao; Zhichun Guo; Yanfang Ye 001; Yozen Liu; Neil Shah; Tong Zhao 003 (NeurIPS, 2024)

Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems. - Matthew Kolodner; Mingxuan Ju; Zihao Fan; Tong Zhao 003; Elham Ghazizadeh; Yan Wu; Neil Shah; Yozen Liu (RobustRecSys@RecSys, 2024)

Improving Embedding-Based Retrieval in Friend Recommendation with ANN Query Expansion. - Pau Perng-Hwa Kung; Zihao Fan; Tong Zhao 003; Yozen Liu; Zhixin Lai; Jiahui Shi; Yan Wu; Jun Yu; Neil Shah; Ganesh Venkataraman (SIGIR, 2024)

The 5th International Workshop on Machine Learning on Graphs (MLoG). - Tyler Derr; Yao Ma 001; Kaize Ding; Tong Zhao 003; Nesreen K. Ahmed (WSDM, 2024)

Neural Scaling Laws on Graphs. - Jingzhe Liu; Haitao Mao; Zhikai Chen; Tong Zhao 003; Neil Shah; Jiliang Tang (CoRR, 2024)

Graph Foundation Models. - Haitao Mao; Zhikai Chen; Wenzhuo Tang; Jianan Zhao 002; Yao Ma 001; Tong Zhao 003; Neil Shah; Mikhail Galkin 001; Jiliang Tang (CoRR, 2024)

Node Duplication Improves Cold-start Link Prediction. - Zhichun Guo; Tong Zhao 003; Yozen Liu; Kaiwen Dong; William Shiao; Neil Shah; Nitesh V. Chawla (CoRR, 2024)

Improving Out-of-Vocabulary Handling in Recommendation Systems. - William Shiao; Mingxuan Ju; Zhichun Guo; Xin Chen 085; Evangelos E. Papalexakis; Tong Zhao 003; Neil Shah; Yozen Liu (CoRR, 2024)

Multimodal Graph Benchmark. - Jing Zhu 005; Yuhang Zhou; Shengyi Qian 001; Zhongmou He; Tong Zhao 003; Neil Shah; Danai Koutra (CoRR, 2024)

Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks. - Rui Xue 006; Tong Zhao 003; Neil Shah; Xiaorui Liu (CoRR, 2024)

HARec: Hyperbolic Graph-LLM Alignment for Exploration and Exploitation in Recommender Systems. - Qiyao Ma; Menglin Yang 001; Mingxuan Ju; Tong Zhao 003; Neil Shah; Rex Ying (CoRR, 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 003; Neil Shah; Jiliang Tang (CoRR, 2024)

Enhancing Item Tokenization for Generative Recommendation through Self-Improvement. - Runjin Chen; Mingxuan Ju; Ngoc Bui; Dimosthenis Antypas; Stanley Cai; Xiaopeng Wu; Leonardo Neves; Zhangyang Wang; Neil Shah; Tong Zhao 003 (CoRR, 2024)

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems. - Xinyi Wu 003; Donald Loveland; Runjin Chen; Yozen Liu; Xin Chen 085; Leonardo Neves; Ali Jadbabaie; Clark Mingxuan Ju; Neil Shah; Tong Zhao 003 (CoRR, 2024)

Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning. - Jing Zhu 005; Yuhang Zhou; Shengyi Qian 001; Zhongmou He; Tong Zhao 003; Neil Shah; Danai Koutra (CVPR, 2025)

Learning Universal User Representations Leveraging Cross-domain User Intent at Snapchat. - Clark Mingxuan Ju; Leonardo Neves; Bhuvesh Kumar; Liam Collins; Tong Zhao 003; Yuwei Qiu; Qing Dou; Yang Zhou; Sohail Nizam; Rengim Aykan Ozturk; Yvette Liu; Sen Yang; et al. (SIGIR, 2025)

Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank. - Donald Loveland; Xinyi Wu 003; Tong Zhao 003; Danai Koutra; Neil Shah; Mingxuan Ju (WWW, 2025)

Improving Out-of-Vocabulary Hashing in Recommendation Systems. - William Shiao; Mingxuan Ju; Zhichun Guo; Xin Chen 085; Evangelos E. Papalexakis; Tong Zhao 003; Neil Shah; Yozen Liu (WWW (Companion Volume), 2025)

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems. - Xinyi Wu 003; Donald Loveland; Runjin Chen; Yozen Liu; Xin Chen 085; Leonardo Neves; Ali Jadbabaie; Mingxuan Ju; Neil Shah; Tong Zhao 003 (WWW, 2025)

Node Duplication Improves Cold-start Link Prediction. - Zhichun Guo; Tong Zhao 003; Yozen Liu; Kaiwen Dong; William Shiao; Mingxuan Ju; Neil Shah; Nitesh V. Chawla (Trans. Mach. Learn. Res., 2025)

Retrieval-Augmented Generation with Graphs (GraphRAG). - Haoyu Han 001; Yu Wang 160; Harry Shomer; Kai Guo 003; Jiayuan Ding; Yongjia Lei; Mahantesh Halappanavar; Ryan A. Rossi; Subhabrata Mukherjee; Xianfeng Tang; Qi He 002; Zhigang Hua; et al. (CoRR, 2025)

GiGL: Large-Scale Graph Neural Networks at Snapchat. - Tong Zhao 003; Yozen Liu; Matthew Kolodner; Kyle Montemayor; Elham Ghazizadeh; Ankit Batra; Zihao Fan; Xiaobin Gao; Xuan Guo; Jiwen Ren; Serim Park; Peicheng Yu; et al. (CoRR, 2025)

Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics. - Jing Zhu 005; Mingxuan Ju; Yozen Liu; Danai Koutra; Neil Shah; Tong Zhao 003 (CoRR, 2025)

Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction. - Zongyue Qin; Shichang Zhang; Mingxuan Ju; Tong Zhao 003; Neil Shah; Yizhou Sun (CoRR, 2025)

On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective. - Donald Loveland; Mingxuan Ju; Tong Zhao 003; Neil Shah; Danai Koutra (CoRR, 2025)

Revisiting Self-attention for Cross-domain Sequential Recommendation. - Clark Mingxuan Ju; Leonardo Neves; Bhuvesh Kumar; Liam Collins; Tong Zhao 003; Yuwei Qiu; Qing Dou; Sohail Nizam; Sen Yang; Neil Shah (CoRR, 2025)

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning. - Ngoc Bui; Menglin Yang 001; Runjin Chen; Leonardo Neves; Mingxuan Ju; Rex Ying; Neil Shah; Tong Zhao 003 (CoRR, 2025)

A Pre-training Framework for Relational Data with Information-theoretic Principles. - Quang Truong; Zhikai Chen; Mingxuan Ju; Tong Zhao 003; Neil Shah; Jiliang Tang (CoRR, 2025)

Generative Recommendation with Semantic IDs: A Practitioner's Handbook. - Clark Mingxuan Ju; Liam Collins; Leonardo Neves; Bhuvesh Kumar; Louis Yufeng Wang; Tong Zhao 003; Neil Shah (CoRR, 2025)