Zheyuan Liu

According to our database, Zheyuan Liu authored at least 24 papers between 2022 and 2025.

Collaborative distances:

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

2025

Incorporating Rather Than Eliminating: Achieving Fairness for Skin Disease Diagnosis Through Group-Specific Expert.

Gelei Xu, Yuying Duan, Zheyuan Liu, Xueyang Li, Meng Jiang, Michael Lemmon, Wei Jin, Yiyu Shi

CoRR, June, 2025

Graph Foundation Models: A Comprehensive Survey.

Zehong Wang, Zheyuan Liu, Tianyi Ma, Jiazheng Li, Zheyuan Zhang, Xingbo Fu, Yiyang Li, Zhengqing Yuan, Wei Song, Yijun Ma, Qingkai Zeng, Xiusi Chen, Jianan Zhao, Jundong Li, Meng Jiang, Pietro Lio, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye

CoRR, May, 2025

Superficial Self-Improved Reasoners Benefit from Model Merging.

Xiangchi Yuan, Chunhui Zhang, Zheyuan Liu, Dachuan Shi, Soroush Vosoughi, Wenke Lee

CoRR, March, 2025

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey.

Bo Ni, Zheyuan Liu, Leyao Wang, Yongjia Lei, Yuying Zhao, Xueqi Cheng, Qingkai Zeng, Luna Dong, Yinglong Xia, Krishnaram Kenthapadi, Ryan A. Rossi, Franck Dernoncourt, Md. Mehrab Tanjim, Nesreen K. Ahmed, Xiaorui Liu, Wenqi Fan, Erik Blasch, Yu Wang, Meng Jiang, Tyler Derr

CoRR, February, 2025

Can Large Language Models Understand Preferences in Personalized Recommendation?

Zhaoxuan Tan, Zinan Zeng, Qingkai Zeng, Zhenyu Wu, Zheyuan Liu, Fengran Mo, Meng Jiang

CoRR, January, 2025

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

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

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Avoiding Copyright Infringement via Large Language Model Unlearning.

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

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

Disentangling Biased Knowledge from Reasoning in Large Language Models via Machine Unlearning.

Zheyuan Liu, Suraj Maharjan, Fanyou Wu, Rahil Parikh, Belhassen Bayar, Srinivasan H. Sengamedu, Meng Jiang

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models.

Zheyuan Liu, Guangyao Dou, Xiangchi Yuan, Chunhui Zhang, Zhaoxuan Tan, Meng Jiang

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

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

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