Zheyuan Liu

According to our database, Zheyuan Liu authored at least 16 papers between 2022 and 2024.

Collaborative distances:

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

2024

CLIPErase: Efficient Unlearning of Visual-Textual Associations in CLIP.

Tianyu Yang, Lisen Dai, Zheyuan Liu, Xiangqi Wang, Meng Jiang, Yapeng Tian, Xiangliang Zhang

CoRR, 2024

Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench.

Zheyuan Liu, Guangyao Dou, Mengzhao Jia, Zhaoxuan Tan, Qingkai Zeng, Yongle Yuan, Meng Jiang

CoRR, 2024

Machine Unlearning in Generative AI: A Survey.

Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang

CoRR, 2024

Avoiding Copyright Infringement via Machine Unlearning.

Guangyao Dou, Zheyuan Liu, Qing Lyu, Kaize Ding, Eric Wong

CoRR, 2024

Graph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm.

Zhiding Liang, Gang Liu, Zheyuan Liu, Jinglei Cheng, Tianyi Hao, Kecheng Liu, Hang Ren, Zhixin Song, Ji Liu, Fanny Ye, Yiyu Shi

CoRR, 2024

UGMAE: A Unified Framework for Graph Masked Autoencoders.

Yijun Tian, Chuxu Zhang, Ziyi Kou, Zheyuan Liu, Xiangliang Zhang, Nitesh V. Chawla

CoRR, 2024

Can we Soft Prompt LLMs for Graph Learning Tasks?

Zheyuan Liu, Xiaoxin He, Yijun Tian, Nitesh V. Chawla

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Breaking the Trilemma of Privacy, Utility, and Efficiency via Controllable Machine Unlearning.

Zheyuan Liu, Guangyao Dou, Eli Chien, Chunhui Zhang, Yijun Tian, Ziwei Zhu

Proceedings of the ACM on Web Conference 2024, 2024

Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts.

Zhaoxuan Tan, Zheyuan Liu, Meng Jiang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning.

Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, Zheyuan Liu, Bing Yin, Meng Jiang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Invited: Graph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm.

Zhiding Liang, Gang Liu, Zheyuan Liu, Jinglei Cheng, Tianyi Hao, Kecheng Liu, Hang Ren, Zhixin Song, Ji Liu, Fanny Ye, Yiyu Shi

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

Towards Safer Large Language Models through Machine Unlearning.

Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning.

Zheyuan Liu, Guangyao Dou, Yijun Tian, Chunhui Zhang, Eli Chien, Ziwei Zhu

CoRR, 2023

Fair Graph Representation Learning via Diverse Mixture-of-Experts.

Zheyuan Liu, Chunhui Zhang, Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, Chuxu Zhang

Proceedings of the ACM Web Conference 2023, 2023

Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization.

Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

GraphBERT: Bridging Graph and Text for Malicious Behavior Detection on Social Media.

Jiele Wu, Chunhui Zhang, Zheyuan Liu, Erchi Zhang, Steven Wilson, Chuxu Zhang

Proceedings of the IEEE International Conference on Data Mining, 2022