Learning Generative Deception Strategies in Combinatorial Masking Games. - Junlin Wu 001; Charles A. Kamhoua; Murat Kantarcioglu; Yevgeniy Vorobeychik (GameSec, 2021)

Robust Deep Reinforcement Learning through Bootstrapped Opportunistic Curriculum. - Junlin Wu 001; Yevgeniy Vorobeychik (ICML, 2022)

Manipulating Elections by Changing Voter Perceptions. - Junlin Wu 001; Andrew Estornell; Lecheng Kong; Yevgeniy Vorobeychik (IJCAI, 2022)

Neural Lyapunov Control for Discrete-Time Systems. - Junlin Wu 001; Andrew Clark 001; Yiannis Kantaros; Yevgeniy Vorobeychik (NeurIPS, 2023)

Exact Verification of ReLU Neural Control Barrier Functions. - Hongchao Zhang; Junlin Wu 001; Yevgeniy Vorobeychik; Andrew Clark 001 (NeurIPS, 2023)

On the Exploitability of Reinforcement Learning with Human Feedback for Large Language Models. - Jiongxiao Wang; Junlin Wu 001; Muhao Chen 001; Yevgeniy Vorobeychik; Chaowei Xiao (CoRR, 2023)

RLHFPoison: Reward Poisoning Attack for Reinforcement Learning with Human Feedback in Large Language Models. - Jiongxiao Wang; Junlin Wu 001; Muhao Chen 001; Yevgeniy Vorobeychik; Chaowei Xiao (ACL (1), 2024)

Verified Safe Reinforcement Learning for Neural Network Dynamic Models. - Junlin Wu 001; Huan Zhang; Yevgeniy Vorobeychik (NeurIPS, 2024)

Axioms for AI Alignment from Human Feedback. - Luise Ge; Daniel Halpern 002; Evi Micha; Ariel D. Procaccia; Itai Shapira; Yevgeniy Vorobeychik; Junlin Wu 001 (NeurIPS, 2024)

Certifying Safety in Reinforcement Learning under Adversarial Perturbation Attacks. - Junlin Wu 001; Hussein Sibai; Yevgeniy Vorobeychik (SP (Workshops), 2024)

Preference Poisoning Attacks on Reward Model Learning. - Junlin Wu 001; Jiongxiao Wang; Chaowei Xiao; Chenguang Wang; Ning Zhang 017; Yevgeniy Vorobeychik (SP, 2025)

Learning Vision-Based Neural Network Controllers with Semi-Probabilistic Safety Guarantees. - Xinhang Ma; Junlin Wu 001; Hussein Sibai; Yiannis Kantaros; Yevgeniy Vorobeychik (CoRR, 2025)