@article{tinyllm,
  title={TinyLLM: Learning a Small Student from Multiple Large Language Models},
  author={Tian, Yijun and Han, Yikun and Chen, Xiusi and Wang, Wei and Chawla, Nitesh V},
  journal={arXiv preprint arXiv:2402.04616},
  year={2024}
}

@inproceedings{gnp,
  title={Graph neural prompting with large language models},
  author={Tian, Yijun and Song, Huan and Wang, Zichen and Wang, Haozhu and Hu, Ziqing and Wang, Fang and Chawla, Nitesh V and Xu, Panpan},
  booktitle={AAAI},
  year={2024}
}

@article{ugmae,
  title={UGMAE: A Unified Framework for Graph Masked Autoencoders},
  author={Tian, Yijun and Zhang, Chuxu and Kou, Ziyi and Liu, Zheyuan and Zhang, Xiangliang and Chawla, Nitesh V},
  journal={arXiv preprint arXiv:2402.08023},
  year={2024}
}

@inproceedings{hgmae,
  title={Heterogeneous Graph Masked Autoencoders},
  author={Tian, Yijun and Dong, Kaiwen and Zhang, Chunhui and Zhang, Chuxu and Chawla, Nitesh V},
  booktitle={AAAI},
  year={2023}
}

@inproceedings{nosmog,
  title={Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency},
  author={Tian, Yijun and Zhang, Chuxu and Guo, Zhichun and Zhang, Xiangliang and Chawla, Nitesh V},
  booktitle={ICLR},
  year={2023}
}

@article{kd_graph_survey,
  title={Knowledge Distillation on Graphs: A Survey},
  author={Tian, Yijun and Pei, Shichao and Zhang, Xiangliang and Zhang, Chuxu and Chawla, Nitesh V},
  journal={arXiv preprint arXiv:2302.00219},
  year={2023}
}

@inproceedings{reciperec,
  title={RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation},
  author={Tian, Yijun and Zhang, Chuxu and Guo, Zhichun and Huang, Chao and Metoyer, Ronald and Chawla, Nitesh V.},
  booktitle={IJCAI},
  year={2022}
}

@inproceedings{recipe2vec,
  title={Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks},
  author={Tian, Yijun and Zhang, Chuxu and Guo, Zhichun and Ma, Yihong and Metoyer, Ronald and Chawla, Nitesh V},
  booktitle={IJCAI},
  year={2022}
}

@article{hgat,
  author={Tian, Yijun and Zhang, Chuxu and Metoyer, Ronald and Chawla, Nitesh V.},   
  title={Recipe Recommendation With Hierarchical Graph Attention Network},  
  journal={Frontiers in Big Data},  
  year={2022}
}

@inproceedings{rn2vec,
  title={Recipe representation learning with networks},
  author={Tian, Yijun and Zhang, Chuxu and Metoyer, Ronald and Chawla, Nitesh V},
  booktitle={CIKM},
  year={2021}
}

@article{gretriever,
  title={G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering},
  author={He, Xiaoxin and Tian, Yijun and Sun, Yifei and Chawla, Nitesh V and Laurent, Thomas and LeCun, Yann and Bresson, Xavier and Hooi, Bryan},
  journal={arXiv preprint arXiv:2402.07630},
  year={2024}
}

@inproceedings{prompt_llm_for_graph,
  title={Can we soft prompt LLMs for graph learning tasks?},
  author={Liu, Zheyuan and He, Xiaoxin and Tian, Yijun and Chawla, Nitesh V},
  booktitle={WWW},
  year={2024}
}

@inproceedings{conmu,
  title={Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning},
  author={Liu, Zheyuan and Dou, Guangyao and Tian, Yijun and Zhang, Chunhui and Chien, Eli and Zhu, Ziwei},
  booktitle={WWW},
  year={2024}
}

@inproceedings{sku,
  title={Towards Safer Large Language Models through Machine Unlearning},
  author={Liu, Zheyuan and Dou, Guangyao and Tan, Zhaoxuan and Tian, Yijun and Jiang, Meng},
  booktitle={ACL},
  year={2024}
}

@article{oppu,
  title={Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning},
  author={Tan, Zhaoxuan and Zeng, Qingkai and Tian, Yijun and Liu, Zheyuan and Yin, Bing and Jiang, Meng},
  journal={arXiv preprint arXiv:2402.04401},
  year={2024}
}

@inproceedings{dragon,
  title={Mitigating Emergent Robustness Degradation while Scaling Graph Learning},
  author={Xiangchi Yuan and Chunhui Zhang and Yijun Tian and Yanfang Ye and Chuxu Zhang},
  booktitle={ICLR},
  year={2024}
}

@inproceedings{mapeppi,
  title={MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding},
  author={Wu, Lirong and Tian, Yijun and Huang, Yufei and Li, Siyuan and Lin, Haitao and Chawla, Nitesh V and Li, Stan Z},
  booktitle={ICLR},
  year={2024}
}

@inproceedings{lime,
  author = {Yuan, Xiangchi and Tian, Yijun and Zhang, Chunhui and Ye, Yanfang and Chawla, Nitesh V. and Zhang, Chuxu},
  title = {Graph Cross Supervised Learning via Generalized Knowledge},
  year = {2024},
  booktitle = {KDD}
}

@article{unlearning_survey,
  title={Machine Unlearning in Generative AI: A Survey},
  author={Liu, Zheyuan and Dou, Guangyao and Tan, Zhaoxuan and Tian, Yijun and Jiang, Meng},
  journal={arXiv preprint arXiv:2407.20516},
  year={2024}
}

@article{llm_ethics_survey,
  title={Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas},
  author={Deng, Chengyuan and Duan, Yiqun and Jin, Xin and Chang, Heng and Tian, Yijun and Liu, Han and Zou, Henry Peng and Jin, Yiqiao and Xiao, Yijia and Wang, Yichen and others},
  journal={arXiv preprint arXiv:2406.05392},
  year={2024}
}

@article{federated_learning_fairness,
  title={Post-Fair Federated Learning: Achieving Group and Community Fairness in Federated Learning via Post-processing},
  author={Duan, Yuying and Tian, Yijun and Chawla, Nitesh and Lemmon, Michael},
  journal={arXiv preprint arXiv:2405.17782},
  year={2024}
}

@inproceedings{promptddg,
  title={Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning},
  author={Wu, Lirong and Tian, Yijun and Lin, Haitao and Huang, Yufei and Li, Siyuan and Chawla, Nitesh V and Li, Stan Z},
  booktitle={ICML},
  year={2024}
}

@inproceedings{podcast2vec,
  title={Structural Podcast Content Modeling with Generalizability},
  author={Tian, Yijun and Aziz, Maryam and Wang, Alice and Palumbo, Enrico and Bouchard, Hugues},
  booktitle={WWW},
  year={2024}
}

@article{zhang2024forecaster,
  title={Forecaster as a Simulator: Simulating Multi-directional Pedestrian Flow with Knowledge-guided Graph Neural Networks},
  author={Zhang, Botao and Xu, Junhao and Lo, Siuming and Zhu, Bin and Tang, Tie-Qiao and Xie, Chuan-Zhi and Tian, Yijun},
  journal={Available at SSRN 4810559},
  year={2024}
}

@article{zhang4861526mixture,
  title={Mixture of Spatial-Temporal Graph Transformer Networks for Urban Congestion Prediction Using Multimodal Data},
  author={Zhang, Jian and Li, Lincan and Chen, Yanyan and Wang, Tao and Xie, Chuan-Zhi Thomas and Tian, Yijun},
  journal={Available at SSRN 4861526},
  year={2024}
}

@inproceedings{sgcl,
  title={S3{GCL}: Spectral, Swift, Spatial Graph Contrastive Learning},
  author={Guancheng Wan and Yijun Tian and Wenke Huang and Nitesh V Chawla and Mang Ye},
  booktitle={ICML},
  year={2024}
}

@article{gnn_crowd_forecast,
  title={Advancing crowd forecasting with graphs across microscopic trajectory to macroscopic dynamics},
  author={Xie, Chuan-Zhi Thomas and Xu, Junhao and Zhu, Bin and Tang, Tie-Qiao and Lo, Siuming and Zhang, Botao and Tian, Yijun},
  journal={Information Fusion},
  year={2024}
}

@article{data_centric_AD_survey,
  title={Data-Centric Evolution in Autonomous Driving: A Comprehensive Survey of Big Data System, Data Mining, and Closed-Loop Technologies},
  author={Li, Lincan and Shao, Wei and Dong, Wei and Tian, Yijun and Yang, Kaixiang and Zhang, Wenjie},
  journal={arXiv preprint arXiv:2401.12888},
  year={2024}
}

@inproceedings{datadec,
  title={When sparsity meets contrastive models: less graph data can bring better class-balanced representations},
  author={Zhang, Chunhui and Huang, Chao and Tian, Yijun and Wen, Qianlong and Ouyang, Zhongyu and Li, Youhuan and Ye, Yanfang and Zhang, Chuxu},
  booktitle={ICML},
  year={2023}
}

@inproceedings{graphdec
  title={Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning},
  author={Chunhui Zhang and Chao Huang and Yijun Tian and Qianlong Wen and Zhongyu Ouyang and Youhuan Li and Yanfang Ye and Chuxu Zhang},
  booktitle={NeurIPS 2022 Workshop: New Frontiers in Graph Learning},
  year={2022}
}

@inproceedings{game,
  title={Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization},
  author={Zhang, Chunhui and Tian, Yijun and Ju, Mingxuan and Liu, Zheyuan and Ye, Yanfang and Chawla, Nitesh and Zhang, Chuxu},
  booktitle={ICLR},
  year={2023}
}

@inproceedings{gfame,
  title={Fair Graph Representation Learning via Diverse Mixture of Experts},
  author={Liu, Zheyuan and Zhang, Chunhui and Tian, Yijun and Zhang, Erchi and Huang, Chao and Ye, Yanfang and Zhang, Chuxu},
  booktitle={WWW},
  year={2023}
}

@inproceedings{bgnn,
  title={Boosting graph neural networks via adaptive knowledge distillation},
  author={Guo, Zhichun and Zhang, Chunhui and Fan, Yujie and Tian, Yijun and Zhang, Chuxu and Chawla, Nitesh V},
  booktitle={AAAI},
  year={2023}
}

@inproceedings{chargrad,
  title={Character as pixels: a controllable prompt adversarial attacking framework for black-box text guided image generation models},
  author={Kou, Ziyi and Pei, Shichao and Tian, Yijun and Zhang, Xiangliang},
  booktitle={IJCAI},
  year={2023}
}

@inproceedings{mol_survey,
  title={Graph-based molecular representation learning},
  author={Guo, Zhichun and Guo, Kehan and Nan, Bozhao and Tian, Yijun and Iyer, Roshni G and Ma, Yihong and Wiest, Olaf and Zhang, Xiangliang and Wang, Wei and Zhang, Chuxu and others},
  booktitle={IJCAI},
  year={2023}
}

@article{imbalance_survey,
  title={Class-Imbalanced Learning on Graphs: A Survey},
  author={Ma, Yihong and Tian, Yijun and Moniz, Nuno and Chawla, Nitesh V},
  journal={arXiv preprint arXiv:2304.04300},
  year={2023}
}

@inproceedings{dragon_workshop,
  title={Navigating Graph Robust Learning against All-Intensity Attacks},
  author={Yuan, Xiangchi and Zhang, Chunhui and Tian, Yijun and Zhang, Chuxu},
  booktitle={The Second Workshop on New Frontiers in Adversarial Machine Learning},
  year={2023}
}

@article{ysmm,
  title={Structural racism and homophobia evaluated through social media sentiment combined with activity spaces and associations with mental health among young sexual minority men},
  author={Duncan, Dustin T and Cook, Stephanie H and Wood, Erica P and Regan, Seann D and Chaix, Basile and Tian, Yijun and Chunara, Rumi},
  journal={Social Science \& Medicine},
  year={2023}
}

@inproceedings{fakeedge,
  title={FakeEdge: Alleviate Dataset Shift in Link Prediction},
  author={Dong, Kaiwen and Tian, Yijun and Guo, Zhichun and Yang, Yang and Chawla, Nitesh},
  booktitle={LoG},
  year={2022}
}

@inproceedings{histgnn,
  title={Hierarchical spatio-temporal graph neural networks for pandemic forecasting},
  author={Ma, Yihong and Gerard, Patrick and Tian, Yijun and Guo, Zhichun and Chawla, Nitesh V},
  booktitle={CIKM},
  year={2022}
}

@inproceedings{tian2020quasi, 
  author={Tian, Yijun and Chunara, Rumi},
  title={Quasi-Experimental Designs for Assessing Response on Social Media to Policy Changes}, 
  booktitle = {ICWSM},
  year = {2020}
}

@article{tian2019geek,
  title={Geek talents: Who are the top experts on github and stack overflow?},
  author={Tian, Yijun and Ng, Waii and Cao, Jialiang and McIntosh, Suzanne},
  journal={Computers, Materials \& Continua},
  year={2019}
}