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ORCIDYijun Tian 0001
Person information
- affiliation: University of Notre Dame, IN, USA
Other persons with the same name
- Yijun Tian 0002 — University of New South Wales, Sydney, NSW, Australia
- Yijun Tian 0003 — New York University, NY, USA
- Yijun Tian 0004
![[0000-0001-8490-1006]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0001-8490-1006")
— Beijing Satellite Navigation Center, China - Yijun Tian 0005 — Henan University of Technology, College of Information Science and Engineering, Zhengzhou, China
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2020 – today
- 2024
[j2]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: 102275 (2024)- [c27]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: 19080-19088 - [c26]Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang:
Towards Safer Large Language Models through Machine Unlearning. ACL (Findings) 2024: 1817-1829 - [c25]Ziyi Kou, Yijun Tian, Meng Jiang, Xiangliang Zhang:
FaDE: A Face Segment Driven Identity Anonymization Framework For Fair Face Recognition. CIKM 2024: 1121-1131 - [c24]Peiyu Li, Xiaobao Huang, Yijun Tian, Nitesh V. Chawla:
ChefFusion: Multimodal Foundation Model Integrating Recipe and Food Image Generation. CIKM 2024: 3872-3876 - [c23]Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, Zheyuan Liu, Bing Yin, Meng Jiang:
Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning. EMNLP 2024: 6476-6491 - [c22]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 - [c21]Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang:
Mitigating Emergent Robustness Degradation while Scaling Graph Learning. ICLR 2024 - [c20]Guancheng Wan, Yijun Tian, Wenke Huang, Nitesh V. Chawla, Mang Ye:
S3GCL: Spectral, Swift, Spatial Graph Contrastive Learning. ICML 2024 - [c19]Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V. Chawla, Stan Z. Li:
Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning. ICML 2024 - [c18]Xiangchi Yuan, Yijun Tian, Chunhui Zhang, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang:
Graph Cross Supervised Learning via Generalized Knowledge. KDD 2024: 4083-4094 - [c17]Zheyuan Liu, Xiaoxin He, Yijun Tian, Nitesh V. Chawla:
Can we Soft Prompt LLMs for Graph Learning Tasks? WWW (Companion Volume) 2024: 481-484 - [c16]Yijun Tian, Maryam Aziz, Alice Wang, Enrico Palumbo, Hugues Bouchard:
Structural Podcast Content Modeling with Generalizability. WWW (Companion Volume) 2024: 710-713 - [c15]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: 1260-1271 - [i26]Lincan Li, Wei Shao, Wei Dong, Yijun Tian, Qiming Zhang, Kaixiang Yang, Wenjie Zhang:
Data-Centric Evolution in Autonomous Driving: A Comprehensive Survey of Big Data System, Data Mining, and Closed-Loop Technologies. CoRR abs/2401.12888 (2024) - [i25]Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, Zheyuan Liu, Bing Yin, Meng Jiang:
Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning. CoRR abs/2402.04401 (2024) - [i24]Yijun Tian, Yikun Han, Xiusi Chen, Wei Wang, Nitesh V. Chawla:
TinyLLM: Learning a Small Student from Multiple Large Language Models. CoRR abs/2402.04616 (2024) - [i23]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 abs/2402.07630 (2024) - [i22]Yijun Tian, Chuxu Zhang, Ziyi Kou, Zheyuan Liu, Xiangliang Zhang, Nitesh V. Chawla:
UGMAE: A Unified Framework for Graph Masked Autoencoders. CoRR abs/2402.08023 (2024) - [i21]Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang:
Towards Safer Large Language Models through Machine Unlearning. CoRR abs/2402.10058 (2024) - [i20]Zheyuan Liu, Xiaoxin He, Yijun Tian, Nitesh V. Chawla:
Can we Soft Prompt LLMs for Graph Learning Tasks? CoRR abs/2402.10359 (2024) - [i19]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 abs/2402.14391 (2024) - [i18]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 abs/2405.10348 (2024) - [i17]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 abs/2405.17782 (2024) - [i16]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 abs/2406.05392 (2024) - [i15]Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang:
Machine Unlearning in Generative AI: A Survey. CoRR abs/2407.20516 (2024) - [i14]Peiyu Li, Xiaobao Huang, Yijun Tian, Nitesh V. Chawla:
ChefFusion: Multimodal Foundation Model Integrating Recipe and Food Image Generation. CoRR abs/2409.12010 (2024) - 2023
- [c14]Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla:
Boosting Graph Neural Networks via Adaptive Knowledge Distillation. AAAI 2023: 7793-7801 - [c13]Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla:
Heterogeneous Graph Masked Autoencoders. AAAI 2023: 9997-10005 - [c12]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 - [c11]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 - [c10]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: 41133-41150 - [c9]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: 983-990 - [c8]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: 6638-6646 - [c7]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: 28-38 - [i13]Yijun Tian, Shichao Pei, Xiangliang Zhang, Chuxu Zhang, Nitesh V. Chawla:
Knowledge Distillation on Graphs: A Survey. CoRR abs/2302.00219 (2023) - [i12]Yihong Ma, Yijun Tian, Nuno Moniz, Nitesh V. Chawla:
Class-Imbalanced Learning on Graphs: A Survey. CoRR abs/2304.04300 (2023) - [i11]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 abs/2309.15427 (2023) - [i10]Zheyuan Liu, Guangyao Dou, Yijun Tian, Chunhui Zhang, Eli Chien, Ziwei Zhu:
Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning. CoRR abs/2310.18574 (2023) - 2022
- [c6]Yihong Ma, Patrick Gérard, Yijun Tian, Zhichun Guo, Nitesh V. Chawla:
Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting. CIKM 2022: 1481-1490 - [c5]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: 3466-3472 - [c4]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: 3473-3479 - [c3]Kaiwen Dong, Yijun Tian, Zhichun Guo, Yang Yang, Nitesh V. Chawla:
FakeEdge: Alleviate Dataset Shift in Link Prediction. LoG 2022: 56 - [i9]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 abs/2205.12396 (2022) - [i8]Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla:
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation. CoRR abs/2205.14005 (2022) - [i7]Zhichun Guo, Bozhao Nan, Yijun Tian, Olaf Wiest, Chuxu Zhang, Nitesh V. Chawla:
Graph-based Molecular Representation Learning. CoRR abs/2207.04869 (2022) - [i6]Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla:
Heterogeneous Graph Masked Autoencoders. CoRR abs/2208.09957 (2022) - [i5]Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla:
NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs. CoRR abs/2208.10010 (2022) - [i4]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 abs/2210.00162 (2022) - [i3]Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla:
Boosting Graph Neural Networks via Adaptive Knowledge Distillation. CoRR abs/2210.05920 (2022) - [i2]Kaiwen Dong, Yijun Tian, Zhichun Guo, Yang Yang, Nitesh V. Chawla:
FakeEdge: Alleviate Dataset Shift in Link Prediction. CoRR abs/2211.15899 (2022) - 2021
- [j1]Yijun Tian, Chuxu Zhang, Ronald A. Metoyer, Nitesh V. Chawla:
Recipe Recommendation With Hierarchical Graph Attention Network. Frontiers Big Data 4: 778417 (2021) - [c2]Yijun Tian, Chuxu Zhang, Ronald A. Metoyer, Nitesh V. Chawla:
Recipe Representation Learning with Networks. CIKM 2021: 1824-1833 - 2020
- [c1]Yijun Tian, Rumi Chunara:
Quasi-Experimental Designs for Assessing Response on Social Media to Policy Changes. ICWSM 2020: 671-682 - [i1]Yijun Tian, Rumi Chunara:
Quasi-experimental Designs for Assessing Response on Social Media to Policy Changes. CoRR abs/2003.13783 (2020)
Coauthor Index
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