Haomin Zhuang

According to our database, Haomin Zhuang authored at least 14 papers between 2023 and 2025.

Collaborative distances:

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

2025

Seeing the Invisible: Machine learning-Based QPI Kernel Extraction via Latent Alignment.

Yingshuai Ji, Haomin Zhuang, Matthew Toole, James McKenzie, Xiaolong Liu, Xiangliang Zhang

CoRR, June, 2025

Dissecting Logical Reasoning in LLMs: A Fine-Grained Evaluation and Supervision Study.

Yujun Zhou, Jiayi Ye, Zipeng Ling, Yufei Han, Yue Huang, Haomin Zhuang, Zhenwen Liang, Kehan Guo, Taicheng Guo, Xiangqi Wang, Xiangliang Zhang

CoRR, June, 2025

SocialMaze: A Benchmark for Evaluating Social Reasoning in Large Language Models.

Zixiang Xu, Yanbo Wang, Yue Huang, Jiayi Ye, Haomin Zhuang, Zirui Song, Lang Gao, Chenxi Wang, Zhaorun Chen, Yujun Zhou, Sixian Li, Wang Pan, Yue Zhao, Jieyu Zhao, Xiangliang Zhang, Xiuying Chen

CoRR, May, 2025

Beyond Single-Value Metrics: Evaluating and Enhancing LLM Unlearning with Cognitive Diagnosis.

Yicheng Lang, Kehan Guo, Yue Huang, Yujun Zhou, Haomin Zhuang, Tianyu Yang, Yao Su, Xiangliang Zhang

CoRR, February, 2025

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs?

Haomin Zhuang, Yihua Zhang, Kehan Guo, Jinghan Jia, Gaowen Liu, Sijia Liu, Xiangliang Zhang

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

Beyond Single-Value Metrics: Evaluating and Enhancing LLM Unlearning with Cognitive Diagnosis.

Yicheng Lang, Kehan Guo, Yue Huang, Yujun Zhou, Haomin Zhuang, Tianyu Yang, Yao Su, Xiangliang Zhang

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

UOE: Unlearning One Expert Is Enough For Mixture-of-experts LLMS.

Haomin Zhuang, Yihua Zhang, Kehan Guo, Jinghan Jia, Gaowen Liu, Sijia Liu, Xiangliang Zhang

CoRR, 2024

Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Yue Huang, Zhengqing Yuan, Yujun Zhou, Kehan Guo, Xiangqi Wang, Haomin Zhuang, Weixiang Sun, Lichao Sun, Jindong Wang, Yanfang Ye, Xiangliang Zhang

CoRR, 2024

Defending Jailbreak Prompts via In-Context Adversarial Game.

Yujun Zhou, Yufei Han, Haomin Zhuang, Taicheng Guo, Kehan Guo, Zhenwen Liang, Hongyan Bao, Xiangliang Zhang

CoRR, 2024

Attack-free Evaluating and Enhancing Adversarial Robustness on Categorical Data.

Yujun Zhou, Yufei Han, Haomin Zhuang, Hongyan Bao, Xiangliang Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Backdoor Federated Learning by Poisoning Backdoor-Critical Layers.

Haomin Zhuang, Mingxian Yu, Hao Wang, Yang Hua, Jian Li, Xu Yuan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Defending Jailbreak Prompts via In-Context Adversarial Game.

Yujun Zhou, Yufei Han, Haomin Zhuang, Kehan Guo, Zhenwen Liang, Hongyan Bao, Xiangliang Zhang

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

2023

A Comparison of Image Denoising Methods.

Zhaoming Kong, Fangxi Deng, Haomin Zhuang, Xiaowei Yang, Jun Yu, Lifang He

CoRR, 2023

A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion.

Haomin Zhuang, Yihua Zhang, Sijia Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023