Into the Reverie: Exploration of the Dream Market. - Theo Carr; Jun Zhuang 004; Dwight Sablan; Emma LaRue; Yubao Wu; Mohammad Al Hasan; George O. Mohler (IEEE BigData, 2019)

Lighter U-net for segmenting white matter hyperintensities in MR images. - Jun Zhuang 004; Mingchen Gao; Mohammad Al Hasan (MobiQuitous, 2019)

Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Networks. - Jun Zhuang 004; Dali Wang (CoRR, 2020)

Anti-perturbation of Online Social Networks by Graph Label Transition. - Jun Zhuang 004; Mohammad Al Hasan (CoRR, 2020)

Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Network. - Jun Zhuang 004; Dali Wang (MICAD, 2021)

Non-exhaustive Learning Using Gaussian Mixture Generative Adversarial Networks. - Jun Zhuang 004; Mohammad Al Hasan (ECML/PKDD (2), 2021)

Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-Supervision. - Jun Zhuang 004; Mohammad Al Hasan (AAAI, 2022)

Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation. - Jun Zhuang 004; Mohammad Al Hasan (CIKM, 2022)

Deperturbation of Online Social Networks via Bayesian Label Transition. - Jun Zhuang 004; Mohammad Al Hasan (SDM, 2022)

How Does Bayesian Noisy Self-Supervision Defend Graph Convolutional Networks? - Jun Zhuang 004; Mohammad Al Hasan (Neural Process. Lett., 2022)

Robust Node Representation Learning via Graph Variational Diffusion Networks. - Jun Zhuang 004; Mohammad Al Hasan (CoRR, 2023)

Trustworthy and Responsible AI for Information and Knowledge Management System. - Huaming Chen; Jun Zhuang 004; Yu Yao 005; Wei Jin 009; Haohan Wang; Yong Xie 002; Chi-Hung Chi; Kim-Kwang Raymond Choo (CIKM, 2024)

Robust Data-centric Graph Structure Learning for Text Classification. - Jun Zhuang 004 (WWW (Companion Volume), 2024)

Understanding Survey Paper Taxonomy about Large Language Models via Graph Representation Learning. - Jun Zhuang 004; Casey Kennington (CoRR, 2024)

Debiasing Machine Unlearning with Counterfactual Examples. - Ziheng Chen 002; Jia Wang 009; Jun Zhuang 004; Abbavaram Gowtham Reddy; Fabrizio Silvestri; Jin Huang 010; Kaushiki Nag; Kun Kuang; Xin Ning 001; Gabriele Tolomei (CoRR, 2024)

Improving Trainability of Variational Quantum Circuits via Regularization Strategies. - Jun Zhuang 004; Jack Cunningham; Chaowen Guan (CoRR, 2024)

Enhancing the Resilience of Graph Neural Networks to Topological Perturbations in Sparse Graphs. - Shuqi He; Jun Zhuang 004; Ding Wang; Luyao Peng; Jun Song (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 001; Han Liu; Henry Peng Zou; Yiqiao Jin; Yijia Xiao; Yichen Wang; Shenghao Wu; Zongxing Xie; et al. (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 004; Haohan Wang (CoRR, 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 004; Jyh-haw Yeh (CoRR, 2024)

Blockchain for Large Language Model Security and Safety: A Holistic Survey. - Caleb Geren; Amanda Board; Gaby G. Dagher; Tim Andersen; Jun Zhuang 004 (SIGKDD Explor., 2024)

NQNN: Noise-Aware Quantum Neural Networks for Medical Image Classification. - Maqsudur Rahman; Jun Zhuang 004 (MICCAI (13), 2025)

Fairness-Aware Graph Representation Learning with Limited Demographic Information. - Zichong Wang; Zhipeng Yin; Liping Yang 002; Jun Zhuang 004; Rui Yu; Qingzhao Kong; Wenbin Zhang 002 (ECML/PKDD (1), 2025)

Large Language Models Can Help Mitigate Barren Plateaus. - Jun Zhuang 004; Chaowen Guan (CoRR, 2025)

Investigating and mitigating barren plateaus in variational quantum circuits: a survey. - Jack Cunningham; Jun Zhuang 004 (Quantum Inf. Process., 2025)

Digital Forensics in the Age of Large Language Models. - Zhipeng Yin; Zichong Wang; Weifeng Xu; Jun Zhuang 004; Pallab Mozumder; Antoinette Smith; Wenbin Zhang 002 (CoRR, 2025)

Exploring the Vulnerability of the Content Moderation Guardrail in Large Language Models via Intent Manipulation. - Jun Zhuang 004; Hai Jin 001; Ye Zhang; Zhengjian Kang; Wenbin Zhang 002; Gaby G. Dagher; Haohan Wang (CoRR, 2025)

InfoFlood: Jailbreaking Large Language Models with Information Overload. - Advait Yadav; Haibo Jin; Man Luo; Jun Zhuang 004; Haohan Wang (CoRR, 2025)

Uncovering the Vulnerability of Large Language Models in the Financial Domain via Risk Concealment. - Gang Cheng; Hai Jin 001; Wenbin Zhang 002; Haohan Wang; Jun Zhuang 004 (CoRR, 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 001; Han Liu; Yichen Wang; Kuofeng Gao; Henry Peng Zou; Yiqiao Jin; Yijia Xiao; Shenghao Wu; et al. (AI Ethics, 2025)