1 citations · 1 across the 9 of their papers we have counts for
11 papers
Sleeping Secrets: How Fine-Tuning Reawakens Privacy Risks in Language Models
Jianhong Li, Jiahao Chen, Yuwen Pu +6
Beyond adapting Large Language Models (LLMs) to specialized applications, fine-tuning has recently been shown to recover private information that is no longer accessible through di…
Safety in Self-Evolving Agents: A Survey
Jiahao Chen, Zhou Feng, Oubo Ma +28
Large language models (LLMs) exhibit strong general capabilities, yet their parameters typically remain fixed after deployment, limiting learning from new interactions. In open-end…
A Finger on the Scale: Covert Policy Steering through Agentic Skills
Jiarui Li, Jiahao Chen, Chunyi Zhou +5
Reusable agent skills extend large language model (LLM) agents with task procedures, tool-use guidance, and output constraints. Yet these skills also act as externalized behavioral…
The Shape of Ownership: Verifying LLM Provenance through Semantic Structures
Zhongrui Sun, Jiahao Chen, Oubo Ma +4
As large language models (LLMs) are increasingly redistributed, adapted, and served behind opaque APIs, model ownership can no longer be established reliably by inspecting model in…
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…
IntraGuard: Committee-Side Defenses Against Review Outsourcing to Commercial Chatbots
Oubo Ma, Ruixiao Lin, Jiahao Chen +3
LLMs become increasingly capable, editorial boards and program committees are growing concerned about reviewers who fully outsource peer review to commercial chatbots. This concern…
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…
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…
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,…
Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?
Yang Dai, Oubo Ma, Longfei Zhang +6
Transformer-based trajectory optimization methods have demonstrated exceptional performance in offline Reinforcement Learning (offline RL). Yet, it poses challenges due to substant…
SUB-PLAY: Adversarial Policies against Partially Observed Multi-Agent Reinforcement Learning Systems
Oubo Ma, Yuwen Pu, Linkang Du +5
Recent advancements in multi-agent reinforcement learning (MARL) have opened up vast application prospects, such as swarm control of drones, collaborative manipulation by robotic a…