Quasi-Experimental Designs for Assessing Response on Social Media to Policy Changes. - Yijun Tian 001; Rumi Chunara (ICWSM, 2020)

Recipe Representation Learning with Networks. - Yijun Tian 001; Chuxu Zhang; Ronald A. Metoyer; Nitesh V. Chawla (CIKM, 2021)

Recipe Recommendation With Hierarchical Graph Attention Network. - Yijun Tian 001; Chuxu Zhang; Ronald A. Metoyer; Nitesh V. Chawla (Frontiers Big Data, 2021)

Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting. - Yihong Ma; Patrick Gérard; Yijun Tian 001; Zhichun Guo; Nitesh V. Chawla (CIKM, 2022)

RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation. - Yijun Tian 001; Chuxu Zhang; Zhichun Guo; Chao Huang 001; Ronald A. Metoyer; Nitesh V. Chawla (IJCAI, 2022)

Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks. - Yijun Tian 001; Chuxu Zhang; Zhichun Guo; Yihong Ma; Ronald A. Metoyer; Nitesh V. Chawla (IJCAI, 2022)

FakeEdge: Alleviate Dataset Shift in Link Prediction. - Kaiwen Dong; Yijun Tian 001; Zhichun Guo; Yang Yang 008; Nitesh V. Chawla (LoG, 2022)

Graph-based Molecular Representation Learning. - Zhichun Guo; Bozhao Nan; Yijun Tian 001; Olaf Wiest; Chuxu Zhang; Nitesh V. Chawla (CoRR, 2022)

NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs. - Yijun Tian 001; Chuxu Zhang; Zhichun Guo; Xiangliang Zhang 001; Nitesh V. Chawla (CoRR, 2022)

Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning. - Chunhui Zhang; Chao Huang 001; Yijun Tian 001; Qianlong Wen; Zhongyu Ouyang; Youhuan Li; Yanfang Ye 001; Chuxu Zhang (CoRR, 2022)

Heterogeneous Graph Masked Autoencoders. - Yijun Tian 001; Kaiwen Dong; Chunhui Zhang; Chuxu Zhang; Nitesh V. Chawla (AAAI, 2023)

Boosting Graph Neural Networks via Adaptive Knowledge Distillation. - Zhichun Guo; Chunhui Zhang; Yujie Fan; Yijun Tian 001; Chuxu Zhang; Nitesh V. Chawla (AAAI, 2023)

Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency. - Yijun Tian 001; Chuxu Zhang; Zhichun Guo; Xiangliang Zhang 001; Nitesh V. Chawla (ICLR, 2023)

Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization. - Chunhui Zhang; Yijun Tian 001; Mingxuan Ju; Zheyuan Liu 010; Yanfang Ye 001; Nitesh V. Chawla; Chuxu Zhang (ICLR, 2023)

When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations. - Chunhui Zhang; Chao Huang 001; Yijun Tian 001; Qianlong Wen; Zhongyu Ouyang; Youhuan Li; Yanfang Ye 001; Chuxu Zhang (ICML, 2023)

Graph-based Molecular Representation Learning. - Zhichun Guo; Kehan Guo; Bozhao Nan; Yijun Tian 001; Roshni G. Iyer; Yihong Ma; Olaf Wiest; Xiangliang Zhang 001; Wei Wang 010; Chuxu Zhang; Nitesh V. Chawla (IJCAI, 2023)

Character As Pixels: A Controllable Prompt Adversarial Attacking Framework for Black-Box Text Guided Image Generation Models. - Ziyi Kou; Shichao Pei; Yijun Tian 001; Xiangliang Zhang 001 (IJCAI, 2023)

Fair Graph Representation Learning via Diverse Mixture-of-Experts. - Zheyuan Liu 010; Chunhui Zhang; Yijun Tian 001; Erchi Zhang; Chao Huang 001; Yanfang Ye 001; Chuxu Zhang (WWW, 2023)

Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning. - Zheyuan Liu 010; Guangyao Dou; Yijun Tian 001; Chunhui Zhang; Eli Chien; Ziwei Zhu 001 (CoRR, 2023)

Graph Neural Prompting with Large Language Models. - Yijun Tian 001; Huan Song; Zichen Wang; Haozhu Wang; Ziqing Hu; Fang Wang; Nitesh V. Chawla; Panpan Xu (AAAI, 2024)

Towards Safer Large Language Models through Machine Unlearning. - Zheyuan Liu 010; Guangyao Dou; Zhaoxuan Tan; Yijun Tian 001; Meng Jiang 001 (ACL (Findings), 2024)

FaDE: A Face Segment Driven Identity Anonymization Framework For Fair Face Recognition. - Ziyi Kou; Yijun Tian 001; Meng Jiang 001; Xiangliang Zhang 001 (CIKM, 2024)

ChefFusion: Multimodal Foundation Model Integrating Recipe and Food Image Generation. - Peiyu Li; Xiaobao Huang; Yijun Tian 001; Nitesh V. Chawla (CIKM, 2024)

Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning. - Zhaoxuan Tan; Qingkai Zeng 001; Yijun Tian 001; Zheyuan Liu 010; Bing Yin; Meng Jiang 001 (EMNLP, 2024)

MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding. - Lirong Wu; Yijun Tian 001; Yufei Huang 002; Siyuan Li 002; Haitao Lin; Nitesh V. Chawla; Stan Z. Li (ICLR, 2024)

Mitigating Emergent Robustness Degradation while Scaling Graph Learning. - Xiangchi Yuan; Chunhui Zhang; Yijun Tian 001; Yanfang Ye 001; Chuxu Zhang (ICLR, 2024)

S3GCL: Spectral, Swift, Spatial Graph Contrastive Learning. - Guancheng Wan; Yijun Tian 001; Wenke Huang; Nitesh V. Chawla; Mang Ye (ICML, 2024)

Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning. - Lirong Wu; Yijun Tian 001; Haitao Lin; Yufei Huang 002; Siyuan Li 002; Nitesh V. Chawla; Stan Z. Li (ICML, 2024)

Graph Cross Supervised Learning via Generalized Knowledge. - Xiangchi Yuan; Yijun Tian 001; Chunhui Zhang; Yanfang Ye 001; Nitesh V. Chawla; Chuxu Zhang (KDD, 2024)

G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. - Xiaoxin He; Yijun Tian 001; Yifei Sun 002; Nitesh V. Chawla; Thomas Laurent 001; Yann LeCun; Xavier Bresson; Bryan Hooi (NeurIPS, 2024)

Breaking the Trilemma of Privacy, Utility, and Efficiency via Controllable Machine Unlearning. - Zheyuan Liu 010; Guangyao Dou; Eli Chien; Chunhui Zhang; Yijun Tian 001; Ziwei Zhu 001 (WWW, 2024)

Can we Soft Prompt LLMs for Graph Learning Tasks? - Zheyuan Liu 010; Xiaoxin He; Yijun Tian 001; Nitesh V. Chawla (WWW (Companion Volume), 2024)

Structural Podcast Content Modeling with Generalizability. - Yijun Tian 001; Maryam Aziz; Alice Wang; Enrico Palumbo; Hugues Bouchard (WWW (Companion Volume), 2024)

Forecaster as a simulator: Simulating multi-directional pedestrian flow with knowledge-guided Graph Neural Networks. - Botao Zhang; Junhao Xu; Chuan-Zhi Thomas Xie; Siuming Lo; Bin Zhu; Tie-Qiao Tang; Yijun Tian 001 (Comput. Ind. Eng., 2024)

Data-Centric Evolution in Autonomous Driving: A Comprehensive Survey of Big Data System, Data Mining, and Closed-Loop Technologies. - Lincan Li; Wei Shao; Wei Dong; Yijun Tian 001; Qiming Zhang; Kaixiang Yang; Wenjie Zhang (CoRR, 2024)

TinyLLM: Learning a Small Student from Multiple Large Language Models. - Yijun Tian 001; Yikun Han; Xiusi Chen; Wei Wang 010; Nitesh V. Chawla (CoRR, 2024)

UGMAE: A Unified Framework for Graph Masked Autoencoders. - Yijun Tian 001; Chuxu Zhang; Ziyi Kou; Zheyuan Liu 010; Xiangliang Zhang 001; Nitesh V. Chawla (CoRR, 2024)

Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning. - Lirong Wu; Yijun Tian 001; Haitao Lin; Yufei Huang 002; Siyuan Li 002; Nitesh V. Chawla; Stan Z. Li (CoRR, 2024)

Post-Fair Federated Learning: Achieving Group and Community Fairness in Federated Learning via Post-processing. - Yuying Duan; Yijun Tian 001; Nitesh V. Chawla; Michael Lemmon 001 (CoRR, 2024)

Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas. - Chengyuan Deng; Yiqun Duan; Xin Jin; Heng Chang; Yijun Tian 001; Han Liu; Henry Peng Zou; Yiqiao Jin; Yijia Xiao; Yichen Wang; Shenghao Wu; Zongxing Xie; et al. (CoRR, 2024)

Machine Unlearning in Generative AI: A Survey. - Zheyuan Liu 010; Guangyao Dou; Zhaoxuan Tan; Yijun Tian 001; Meng Jiang 001 (CoRR, 2024)

Advancing crowd forecasting with graphs across microscopic trajectory to macroscopic dynamics. - Chuan-Zhi Thomas Xie; Junhao Xu; Bin Zhu; Tie-Qiao Tang; Siuming Lo; Botao Zhang; Yijun Tian 001 (Inf. Fusion, 2024)

Beyond Answers: Transferring Reasoning Capabilities to Smaller LLMs Using Multi-Teacher Knowledge Distillation. - Yijun Tian 001; Yikun Han; Xiusi Chen; Wei Wang 010; Nitesh V. Chawla (WSDM, 2025)

Mixture of Spatial-Temporal Graph Transformer Networks for urban congestion prediction using multimodal transportation data. - Jian Zhang 088; Yanyan Chen; Tao Wang; Chuan-Zhi Thomas Xie; Yijun Tian 001 (Expert Syst. Appl., 2025)

SDRT: Enhance Vision-Language Models by Self-Distillation with Diverse Reasoning Traces. - Guande Wu; Huan Song; Yawei Wang; Qiaojing Yan; Yijun Tian 001; Lin Lee Cheong; Panpan Xu (CoRR, 2025)

MV-Debate: Multi-view Agent Debate with Dynamic Reflection Gating for Multimodal Harmful Content Detection in Social Media. - Rui Lu; Jinhe Bi; Yunpu Ma; Feng Xiao; Yuntao Du 001; Yijun Tian 001 (CoRR, 2025)

Class-Imbalanced Learning on Graphs: A Survey. - Yihong Ma; Yijun Tian 001; Nuno Moniz; Nitesh V. Chawla (ACM Comput. Surv., 2025)

Knowledge Distillation on Graphs: A Survey. - Yijun Tian 001; Shichao Pei; Xiangliang Zhang 001; Chuxu Zhang; Nitesh V. Chawla (ACM Comput. Surv., 2025)