collaborators

5 papers

cs.LG2026

TrojanTO: Action-Level Backdoor Attacks against Trajectory Optimization Models

Yang Dai, Oubo Ma, Longfei Zhang +6

Recent advances in Trajectory Optimization (TO) models have achieved remarkable success in offline reinforcement learning. However, their vulnerabilities against backdoor attacks a…

cs.LG2026

Angel or Demon: Investigating the Plasticity Interventions' Impact on Backdoor Threats in Deep Reinforcement Learning

Oubo Ma, Ruixiao Lin, Yang Dai +4

Extensive research has highlighted the severe threats posed by backdoor attacks to deep reinforcement learning (DRL). However, prior studies primarily focus on vanilla scenarios, w…

cs.CR2026

Shattering the Echo Chamber: Hidden Safeguards in Manuscripts Against the AI Takeover of Peer Review

Oubo Ma, Ruixiao Lin, Jiahao Chen +3

As LLMs become increasingly capable, editorial boards and program committees are growing concerned about reviewers who fully outsource peer review to commercial chatbots. This conc…

cs.LG2025

Reformulation is All You Need: Addressing Malicious Text Features in DNNs

Yi Jiang, Oubo Ma, Yong Yang +2

Human language encompasses a wide range of intricate and diverse implicit features, which attackers can exploit to launch adversarial or backdoor attacks, compromising DNN models f…

cs.LG2025

UNIDOOR: A Universal Framework for Action-Level Backdoor Attacks in Deep Reinforcement Learning

Oubo Ma, Linkang Du, Yang Dai +4

Deep reinforcement learning (DRL) is widely applied to safety-critical decision-making scenarios. However, DRL is vulnerable to backdoor attacks, especially action-level backdoors,…