Yijun Tian

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 46

Top Topics

Image Generation

Graph Representation

Experimental Designs

Protein Interaction

Top Venues

Publications

Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang
Machine Unlearning in Generative AI: A Survey. CoRR (2024)
Xiangchi Yuan, Yijun Tian, Chunhui Zhang, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang
Graph Cross Supervised Learning via Generalized Knowledge. KDD (2024)
Yijun Tian, Chuxu Zhang, Ziyi Kou, Zheyuan Liu, Xiangliang Zhang, Nitesh V. Chawla
UGMAE: A Unified Framework for Graph Masked Autoencoders. CoRR (2024)
Yijun Tian, Huan Song, Zichen Wang, Haozhu Wang, Ziqing Hu, Fang Wang, Nitesh V. Chawla, Panpan Xu
Graph Neural Prompting with Large Language Models. AAAI (2024)
Yijun Tian, Maryam Aziz, Alice Wang, Enrico Palumbo, Hugues Bouchard
Structural Podcast Content Modeling with Generalizability. WWW (Companion Volume) (2024)
Chengyuan Deng, Yiqun Duan, Xin Jin, Heng Chang, Yijun Tian, Han Liu, Henry Peng Zou, Yiqiao Jin, Yijia Xiao, Yichen Wang, Shenghao Wu, Zongxing Xie, Kuofeng Gao, Sihong He, Jun Zhuang, Lu Cheng, Haohan Wang
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas. CoRR (2024)
Zheyuan Liu, Guangyao Dou, Eli Chien, Chunhui Zhang, Yijun Tian, Ziwei Zhu
Breaking the Trilemma of Privacy, Utility, and Efficiency via Controllable Machine Unlearning. WWW (2024)
Chuan-Zhi Thomas Xie, Junhao Xu, Bin Zhu, Tie-Qiao Tang, Siuming Lo, Botao Zhang, Yijun Tian
Advancing crowd forecasting with graphs across microscopic trajectory to macroscopic dynamics. Inf. Fusion 106 (2024)
Yuying Duan, Yijun Tian, Nitesh V. Chawla, Michael Lemmon
Post-Fair Federated Learning: Achieving Group and Community Fairness in Federated Learning via Post-processing. CoRR (2024)
Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang
Towards Safer Large Language Models through Machine Unlearning. ACL (Findings) (2024)
Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh V. Chawla, Stan Z. Li
MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding. CoRR (2024)
Zheyuan Liu, Xiaoxin He, Yijun Tian, Nitesh V. Chawla
Can we Soft Prompt LLMs for Graph Learning Tasks? WWW (Companion Volume) (2024)
Zheyuan Liu, Xiaoxin He, Yijun Tian, Nitesh V. Chawla
Can we soft prompt LLMs for graph learning tasks? CoRR (2024)
Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh V. Chawla, Stan Z. Li
MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding. ICLR (2024)
Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang
Mitigating Emergent Robustness Degradation while Scaling Graph Learning. ICLR (2024)
Yijun Tian, Yikun Han, Xiusi Chen, Wei Wang, Nitesh V. Chawla
TinyLLM: Learning a Small Student from Multiple Large Language Models. CoRR (2024)
Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V. Chawla, Stan Z. Li
Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning. CoRR (2024)
Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. CoRR (2024)
Yihong Ma, Yijun Tian, Nuno Moniz, Nitesh V. Chawla
Class-Imbalanced Learning on Graphs: A Survey. CoRR (2023)
Zheyuan Liu, Chunhui Zhang, Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, Chuxu Zhang
Fair Graph Representation Learning via Diverse Mixture-of-Experts. WWW (2023)
Zhichun Guo, Kehan Guo, Bozhao Nan, Yijun Tian, Roshni G. Iyer, Yihong Ma, Olaf Wiest, Xiangliang Zhang, Wei Wang, Chuxu Zhang, Nitesh V. Chawla
Graph-based Molecular Representation Learning. IJCAI (2023)
Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang
When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations. ICML (2023)
Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang
Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization. ICLR (2023)
Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla
Boosting Graph Neural Networks via Adaptive Knowledge Distillation. AAAI (2023)
Ziyi Kou, Shichao Pei, Yijun Tian, Xiangliang Zhang
Character As Pixels: A Controllable Prompt Adversarial Attacking Framework for Black-Box Text Guided Image Generation Models. IJCAI (2023)
Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla
Heterogeneous Graph Masked Autoencoders. AAAI (2023)
Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla
Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency. ICLR (2023)
Yijun Tian, Huan Song, Zichen Wang, Haozhu Wang, Ziqing Hu, Fang Wang, Nitesh V. Chawla, Panpan Xu
Graph Neural Prompting with Large Language Models. CoRR (2023)
Yijun Tian, Shichao Pei, Xiangliang Zhang, Chuxu Zhang, Nitesh V. Chawla
Knowledge Distillation on Graphs: A Survey. CoRR (2023)
Zheyuan Liu, Guangyao Dou, Yijun Tian, Chunhui Zhang, Eli Chien, Ziwei Zhu
Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning. CoRR (2023)
Yihong Ma, Patrick Gérard, Yijun Tian, Zhichun Guo, Nitesh V. Chawla
Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting. CIKM (2022)
Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang
Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning. CoRR (2022)
Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla
Heterogeneous Graph Masked Autoencoders. CoRR (2022)
Kaiwen Dong, Yijun Tian, Zhichun Guo, Yang Yang, Nitesh V. Chawla
FakeEdge: Alleviate Dataset Shift in Link Prediction. LoG (2022)
Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla
NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs. CoRR (2022)
Zhichun Guo, Bozhao Nan, Yijun Tian, Olaf Wiest, Chuxu Zhang, Nitesh V. Chawla
Graph-based Molecular Representation Learning. CoRR (2022)
Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla
Boosting Graph Neural Networks via Adaptive Knowledge Distillation. CoRR (2022)
Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation. CoRR (2022)
Kaiwen Dong, Yijun Tian, Zhichun Guo, Yang Yang, Nitesh V. Chawla
FakeEdge: Alleviate Dataset Shift in Link Prediction. CoRR (2022)
Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation. IJCAI (2022)
Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla
Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks. IJCAI (2022)
Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla
Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks. CoRR (2022)
Yijun Tian, Chuxu Zhang, Ronald A. Metoyer, Nitesh V. Chawla
Recipe Representation Learning with Networks. CIKM (2021)
Yijun Tian, Chuxu Zhang, Ronald A. Metoyer, Nitesh V. Chawla
Recipe Recommendation With Hierarchical Graph Attention Network. Frontiers Big Data 4 (2021)
Yijun Tian, Rumi Chunara
Quasi-experimental Designs for Assessing Response on Social Media to Policy Changes. CoRR (2020)
Yijun Tian, Rumi Chunara
Quasi-Experimental Designs for Assessing Response on Social Media to Policy Changes. ICWSM (2020)