Jun Zhuang

According to our database, Jun Zhuang authored at least 30 papers between 2019 and 2025.

Collaborative distances:

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

2025

Deconstructing the ethics of large language models from long-standing issues to new-emerging dilemmas: a survey.

Chengyuan Deng, Yiqun Duan, Xin Jin, Heng Chang, Yijun Tian, Han Liu, Yichen Wang, Kuofeng Gao, Henry Peng Zou, Yiqiao Jin, Yijia Xiao, Shenghao Wu, Zongxing Xie, Weimin Lyu, Sihong He, Lu Cheng, Haohan Wang, Jun Zhuang

AI Ethics, October, 2025

Uncovering the Vulnerability of Large Language Models in the Financial Domain via Risk Concealment.

Gang Cheng, Hai Jin, Wenbin Zhang, Haohan Wang, Jun Zhuang

CoRR, September, 2025

InfoFlood: Jailbreaking Large Language Models with Information Overload.

Advait Yadav, Haibo Jin, Man Luo, Jun Zhuang, Haohan Wang

CoRR, June, 2025

Exploring the Vulnerability of the Content Moderation Guardrail in Large Language Models via Intent Manipulation.

Jun Zhuang, Hai Jin, Ye Zhang, Zhengjian Kang, Wenbin Zhang, Gaby G. Dagher, Haohan Wang

CoRR, May, 2025

Digital Forensics in the Age of Large Language Models.

Zhipeng Yin, Zichong Wang, Weifeng Xu, Jun Zhuang, Pallab Mozumder, Antoinette Smith, Wenbin Zhang

CoRR, April, 2025

Investigating and mitigating barren plateaus in variational quantum circuits: a survey.

Jack Cunningham, Jun Zhuang

Quantum Inf. Process., February, 2025

Large Language Models Can Help Mitigate Barren Plateaus.

Jun Zhuang, Chaowen Guan

CoRR, February, 2025

Fairness-Aware Graph Representation Learning with Limited Demographic Information.

Zichong Wang, Zhipeng Yin, Liping Yang, Jun Zhuang, Rui Yu, Qingzhao Kong, Wenbin Zhang

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

NQNN: Noise-Aware Quantum Neural Networks for Medical Image Classification.

Maqsudur Rahman, Jun Zhuang

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025

2024

Blockchain for Large Language Model Security and Safety: A Holistic Survey.

Caleb Geren, Amanda Board, Gaby G. Dagher, Tim Andersen, Jun Zhuang

SIGKDD Explor., December, 2024

A Survey on the Application of Generative Adversarial Networks in Cybersecurity: Prospective, Direction and Open Research Scopes.

Md Mashrur Arifin, Md Shoaib Ahmed, Tanmai Kumar Ghosh, Jun Zhuang, Jyh-haw Yeh

CoRR, 2024

JailbreakZoo: Survey, Landscapes, and Horizons in Jailbreaking Large Language and Vision-Language Models.

Haibo Jin, Leyang Hu, Xinuo Li, Peiyan Zhang, Chonghan Chen, Jun Zhuang, Haohan Wang

CoRR, 2024

Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas.

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

CoRR, 2024

Enhancing the Resilience of Graph Neural Networks to Topological Perturbations in Sparse Graphs.

Shuqi He, Jun Zhuang, Ding Wang, Luyao Peng, Jun Song

CoRR, 2024

Improving Trainability of Variational Quantum Circuits via Regularization Strategies.

Jun Zhuang, Jack Cunningham, Chaowen Guan

CoRR, 2024

Debiasing Machine Unlearning with Counterfactual Examples.

Ziheng Chen, Jia Wang, Jun Zhuang, Abbavaram Gowtham Reddy, Fabrizio Silvestri, Jin Huang, Kaushiki Nag, Kun Kuang, Xin Ning, Gabriele Tolomei

CoRR, 2024

Understanding Survey Paper Taxonomy about Large Language Models via Graph Representation Learning.

Jun Zhuang, Casey Kennington

CoRR, 2024

Robust Data-centric Graph Structure Learning for Text Classification.

Jun Zhuang

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

Trustworthy and Responsible AI for Information and Knowledge Management System.

Huaming Chen, Jun Zhuang, Yu Yao, Wei Jin, Haohan Wang, Yong Xie, Chi-Hung Chi, Kim-Kwang Raymond Choo

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Robust Node Representation Learning via Graph Variational Diffusion Networks.

Jun Zhuang, Mohammad Al Hasan

CoRR, 2023

2022

How Does Bayesian Noisy Self-Supervision Defend Graph Convolutional Networks?

Jun Zhuang, Mohammad Al Hasan

Neural Process. Lett., 2022

Deperturbation of Online Social Networks via Bayesian Label Transition.

Jun Zhuang, Mohammad Al Hasan

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation.

Jun Zhuang, Mohammad Al Hasan

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-Supervision.

Jun Zhuang, Mohammad Al Hasan

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Non-exhaustive Learning Using Gaussian Mixture Generative Adversarial Networks.

Jun Zhuang, Mohammad Al Hasan

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Network.

Jun Zhuang, Dali Wang

Proceedings of 2021 International Conference on Medical Imaging and Computer-Aided Diagnosis, 2021

2020

Anti-perturbation of Online Social Networks by Graph Label Transition.

Jun Zhuang, Mohammad Al Hasan

CoRR, 2020

Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Networks.

Jun Zhuang, Dali Wang

CoRR, 2020

2019

Lighter U-net for segmenting white matter hyperintensities in MR images.

Jun Zhuang, Mingchen Gao, Mohammad Al Hasan

Proceedings of the MobiQuitous 2019, 2019

Into the Reverie: Exploration of the Dream Market.

Theo Carr, Jun Zhuang, Dwight Sablan, Emma LaRue, Yubao Wu, Mohammad Al Hasan, George O. Mohler

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019