Tong Zhao

According to our database, Tong Zhao authored at least 80 papers between 2018 and 2025.

Collaborative distances:

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

2025

Generative Recommendation with Semantic IDs: A Practitioner's Handbook.

Clark Mingxuan Ju, Liam Collins, Leonardo Neves, Bhuvesh Kumar, Louis Yufeng Wang, Tong Zhao, Neil Shah

CoRR, July, 2025

A Pre-training Framework for Relational Data with Information-theoretic Principles.

Quang Truong, Zhikai Chen, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang

CoRR, July, 2025

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning.

Ngoc Bui, Menglin Yang, Runjin Chen, Leonardo Neves, Mingxuan Ju, Rex Ying, Neil Shah, Tong Zhao

CoRR, June, 2025

Revisiting Self-attention for Cross-domain Sequential Recommendation.

Clark Mingxuan Ju, Leonardo Neves, Bhuvesh Kumar, Liam Collins, Tong Zhao, Yuwei Qiu, Qing Dou, Sohail Nizam, Sen Yang, Neil Shah

CoRR, May, 2025

On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective.

Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Danai Koutra

CoRR, May, 2025

Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction.

Zongyue Qin, Shichang Zhang, Mingxuan Ju, Tong Zhao, Neil Shah, Yizhou Sun

CoRR, April, 2025

Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics.

Jing Zhu, Mingxuan Ju, Yozen Liu, Danai Koutra, Neil Shah, Tong Zhao

CoRR, March, 2025

GiGL: Large-Scale Graph Neural Networks at Snapchat.

Tong Zhao, Yozen Liu, Matthew Kolodner, Kyle Montemayor, Elham Ghazizadeh, Ankit Batra, Zihao Fan, Xiaobin Gao, Xuan Guo, Jiwen Ren, Serim Park, Peicheng Yu, Jun Yu, Shubham Vij, Neil Shah

CoRR, February, 2025

Retrieval-Augmented Generation with Graphs (GraphRAG).

Haoyu Han, Yu Wang, Harry Shomer, Kai Guo, Jiayuan Ding, Yongjia Lei, Mahantesh Halappanavar, Ryan A. Rossi, Subhabrata Mukherjee, Xianfeng Tang, Qi He, Zhigang Hua, Bo Long, Tong Zhao, Neil Shah, Amin Javari, Yinglong Xia, Jiliang Tang

CoRR, January, 2025

Node Duplication Improves Cold-start Link Prediction.

Zhichun Guo, Tong Zhao, Yozen Liu, Kaiwen Dong, William Shiao, Mingxuan Ju, Neil Shah, Nitesh V. Chawla

Trans. Mach. Learn. Res., 2025

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems.

Xinyi Wu, Donald Loveland, Runjin Chen, Yozen Liu, Xin Chen, Leonardo Neves, Ali Jadbabaie, Mingxuan Ju, Neil Shah, Tong Zhao

Proceedings of the ACM on Web Conference 2025, 2025

Improving Out-of-Vocabulary Hashing in Recommendation Systems.

William Shiao, Mingxuan Ju, Zhichun Guo, Xin Chen, Evangelos E. Papalexakis, Tong Zhao, Neil Shah, Yozen Liu

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank.

Donald Loveland, Xinyi Wu, Tong Zhao, Danai Koutra, Neil Shah, Mingxuan Ju

Proceedings of the ACM on Web Conference 2025, 2025

Learning Universal User Representations Leveraging Cross-domain User Intent at Snapchat.

Clark Mingxuan Ju, Leonardo Neves, Bhuvesh Kumar, Liam Collins, Tong Zhao, Yuwei Qiu, Qing Dou, Yang Zhou, Sohail Nizam, Rengim Aykan Ozturk, Yvette Liu, Sen Yang, Manish Malik, Neil Shah

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning.

Jing Zhu, Yuhang Zhou, Shengyi Qian, Zhongmou He, Tong Zhao, Neil Shah, Danai Koutra

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

GraphHash: Graph Clustering Enables Parameter Efficiency in Recommender Systems.

Xinyi Wu, Donald Loveland, Runjin Chen, Yozen Liu, Xin Chen, Leonardo Neves, Ali Jadbabaie, Clark Mingxuan Ju, Neil Shah, Tong Zhao

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

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, Neil Shah, Jiliang Tang

CoRR, 2024

HARec: Hyperbolic Graph-LLM Alignment for Exploration and Exploitation in Recommender Systems.

Qiyao Ma, Menglin Yang, Mingxuan Ju, Tong Zhao, Neil Shah, Rex Ying

CoRR, 2024

Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks.

Rui Xue, Tong Zhao, Neil Shah, Xiaorui Liu

CoRR, 2024

Multimodal Graph Benchmark.

Jing Zhu, Yuhang Zhou, Shengyi Qian, Zhongmou He, Tong Zhao, Neil Shah, Danai Koutra

CoRR, 2024

Improving Out-of-Vocabulary Handling in Recommendation Systems.

William Shiao, Mingxuan Ju, Zhichun Guo, Xin Chen, Evangelos E. Papalexakis, Tong Zhao, Neil Shah, Yozen Liu

CoRR, 2024

Node Duplication Improves Cold-start Link Prediction.

Zhichun Guo, Tong Zhao, Yozen Liu, Kaiwen Dong, William Shiao, Neil Shah, Nitesh V. Chawla

CoRR, 2024

Graph Foundation Models.

Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang

CoRR, 2024

Neural Scaling Laws on Graphs.

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

CoRR, 2024

The 5th International Workshop on Machine Learning on Graphs (MLoG).

Tyler Derr, Yao Ma, Kaize Ding, Tong Zhao, Nesreen K. Ahmed

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Improving Embedding-Based Retrieval in Friend Recommendation with ANN Query Expansion.

Pau Perng-Hwa Kung, Zihao Fan, Tong Zhao, Yozen Liu, Zhixin Lai, Jiahui Shi, Yan Wu, Jun Yu, Neil Shah, Ganesh Venkataraman

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems.

Matthew Kolodner, Mingxuan Ju, Zihao Fan, Tong Zhao, Elham Ghazizadeh, Yan Wu, Neil Shah, Yozen Liu

Proceedings of the Workshop Design, 2024

How Does Message Passing Improve Collaborative Filtering?

Mingxuan Ju, William Shiao, Zhichun Guo, Yanfang Ye, Yozen Liu, Neil Shah, Tong Zhao

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

Position: Graph Foundation Models Are Already Here.

Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

LLaGA: Large Language and Graph Assistant.

Runjin Chen, Tong Zhao, Ajay Kumar Jaiswal, Neil Shah, Zhangyang Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Revisiting Link Prediction: a data perspective.

Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

A Topological Perspective on Demystifying GNN-Based Link Prediction Performance.

Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning from Graphs Beyond Message Passing Neural Networks.

Tong Zhao, Neil Shah, Elham Ghazizadeh

Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

2023

Deep Multimodal Complementarity Learning.

Daheng Wang, Tong Zhao, Wenhao Yu, Nitesh V. Chawla, Meng Jiang

IEEE Trans. Neural Networks Learn. Syst., December, 2023

Modeling Co-Evolution of Attributed and Structural Information in Graph Sequence.

Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang

IEEE Trans. Knowl. Data Eng., 2023

Graph Data Augmentation for Graph Machine Learning: A Survey.

Tong Zhao, Wei Jin, Yozen Liu, Yingheng Wang, Gang Liu, Stephan Günnemann, Neil Shah, Meng Jiang

IEEE Data Eng. Bull., 2023

Graph Transformers for Large Graphs.

Vijay Prakash Dwivedi, Yozen Liu, Anh Tuan Luu, Xavier Bresson, Neil Shah, Tong Zhao

CoRR, 2023

Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?

Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Data-Centric Learning from Unlabeled Graphs with Diffusion Model.

Gang Liu, Eric Inae, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation.

Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Large-Scale Graph Neural Networks: The Past and New Frontiers.

Rui Xue, Haoyu Han, Tong Zhao, Neil Shah, Jiliang Tang, Xiaorui Liu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

CARL-G: Clustering-Accelerated Representation Learning on Graphs.

William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Semi-Supervised Graph Imbalanced Regression.

Gang Liu, Tong Zhao, Eric Inae, Tengfei Luo, Meng Jiang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Linkless Link Prediction via Relational Distillation.

Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh V. Chawla, Neil Shah, Tong Zhao

Proceedings of the International Conference on Machine Learning, 2023

Link Prediction with Non-Contrastive Learning.

William Shiao, Zhichun Guo, Tong Zhao, Evangelos E. Papalexakis, Yozen Liu, Neil Shah

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization.

Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization.

Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Empowering Graph Representation Learning with Test-Time Graph Transformation.

Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

A Synergistic Approach for Graph Anomaly Detection With Pattern Mining and Feature Learning.

Tong Zhao, Tianwen Jiang, Neil Shah, Meng Jiang

IEEE Trans. Neural Networks Learn. Syst., 2022

Federated Dynamic Graph Neural Networks with Secure Aggregation for Video-based Distributed Surveillance.

Meng Jiang, Taeho Jung, Ryan Karl, Tong Zhao

ACM Trans. Intell. Syst. Technol., 2022

Graph Data Augmentation for Graph Machine Learning: A Survey.

Tong Zhao, Gang Liu, Stephan Günnemann, Meng Jiang

CoRR, 2022

Neural-PDE: a RNN based neural network for solving time dependent PDEs.

Yihao Hu, Tong Zhao, Shixin Xu, Lizhen Lin, Zhiliang Xu

Commun. Inf. Syst., 2022

AutoGDA: Automated Graph Data Augmentation for Node Classification.

Tong Zhao, Xianfeng Tang, Danqing Zhang, Haoming Jiang, Nikhil Rao, Yiwei Song, Pallav Agrawal, Karthik Subbian, Bing Yin, Meng Jiang

Proceedings of the Learning on Graphs Conference, 2022

Flashlight: Scalable Link Prediction With Effective Decoders.

Yiwei Wang, Bryan Hooi, Yozen Liu, Tong Zhao, Zhichun Guo, Neil Shah

Proceedings of the Learning on Graphs Conference, 2022

Graph Rationalization with Environment-based Augmentations.

Gang Liu, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Learning from Counterfactual Links for Link Prediction.

Tong Zhao, Gang Liu, Daheng Wang, Wenhao Yu, Meng Jiang

Proceedings of the International Conference on Machine Learning, 2022

Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering.

Mingxuan Ju, Wenhao Yu, Tong Zhao, Chuxu Zhang, Yanfang Ye

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts.

Wenhao Yu, Chenguang Zhu, Lianhui Qin, Zhihan Zhang, Tong Zhao, Meng Jiang

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Biomedical Knowledge Graphs Construction From Conditional Statements.

Tianwen Jiang, Qingkai Zeng, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang

IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Counterfactual Graph Learning for Link Prediction.

Tong Zhao, Gang Liu, Daheng Wang, Wenhao Yu, Meng Jiang

CoRR, 2021

Dynamic Attributed Graph Prediction with Conditional Normalizing Flows.

Daheng Wang, Tong Zhao, Nitesh V. Chawla, Meng Jiang

Proceedings of the IEEE International Conference on Data Mining, 2021

Sentence-Permuted Paragraph Generation.

Wenhao Yu, Chenguang Zhu, Tong Zhao, Zhichun Guo, Meng Jiang

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Action Sequence Augmentation for Early Graph-based Anomaly Detection.

Tong Zhao, Bo Ni, Wenhao Yu, Zhichun Guo, Neil Shah, Meng Jiang

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

A Unified View on Graph Neural Networks as Graph Signal Denoising.

Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Data Augmentation for Graph Neural Networks.

Tong Zhao, Yozen Liu, Leonardo Neves, Oliver J. Woodford, Meng Jiang, Neil Shah

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Early Anomaly Detection by Learning and Forecasting Behavior.

Tong Zhao, Bo Ni, Wenhao Yu, Meng Jiang

CoRR, 2020

Federated Dynamic GNN with Secure Aggregation.

Meng Jiang, Taeho Jung, Ryan Karl, Tong Zhao

CoRR, 2020

Neural Time-Dependent Partial Differential Equation.

Yihao Hu, Tong Zhao, Zhiliang Xu, Lizhen Lin

CoRR, 2020

Learning Attribute-Structure Co-Evolutions in Dynamic Graphs.

Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang

CoRR, 2020

Canonicalizing Open Knowledge Bases with Multi-Layered Meta-Graph Neural Network.

Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang

CoRR, 2020

A Probabilistic Model with Commonsense Constraints for Pattern-based Temporal Fact Extraction.

Yang Zhou, Tong Zhao, Meng Jiang

CoRR, 2020

Identifying Referential Intention with Heterogeneous Contexts.

Wenhao Yu, Mengxia Yu, Tong Zhao, Meng Jiang

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Error-Bounded Graph Anomaly Loss for GNNs.

Tong Zhao, Chuchen Deng, Kaifeng Yu, Tianwen Jiang, Daheng Wang, Meng Jiang

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

Constructing Information-Lossless Biological Knowledge Graphs from Conditional Statements.

Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang

CoRR, 2019

The Role of: A Novel Scientific Knowledge Graph Representation and Construction Model.

Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Multi-Input Multi-Output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text.

Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

CTGA: Graph-based Biomedical Literature Search.

Tianwen Jiang, Zhihan Zhang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018

Actionable Objective Optimization for Suspicious Behavior Detection on Large Bipartite Graphs.

Tong Zhao, Matthew Malir, Meng Jiang

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018