14 papers
VLESA: Vision-Language Embodied Safety Agent for Human Activity Monitoring
Hanjiang Hu, Yiyuan Pan, Jiaxing Li +5
As AI systems increasingly assist humans in physical tasks, ensuring safety becomes paramount -- physical actions carry immediate and irreversible consequences that digital errors…
Stateful Online Monitoring Catches Distributed Agent Attacks
Davis Brown, Samarth Bhargav, Arav Santhanam +7
Language models can find thousands of severe software vulnerabilities, and agents are increasingly being misused for cyberattacks. To avoid detection, attackers frequently distribu…
Benchmarking Misuse Mitigation Against Covert Adversaries
Davis Brown, Mahdi Sabbaghi, Luze Sun +4
Existing language model safety evaluations focus on overt attacks and low-stakes tasks. In reality, an attacker can easily subvert existing safeguards by requesting help on small,…
Safety Guardrails for LLM-Enabled Robots
Zachary Ravichandran, Alexander Robey, Vijay Kumar +2
Although the integration of large language models (LLMs) into robotics has unlocked transformative capabilities, it has also introduced significant safety concerns, ranging from av…
Contextual Safety Reasoning and Grounding for Open-World Robots
Zachary Ravichandran, David Snyder, Alexander Robey +3
Robots are increasingly operating in open-world environments where safe behavior depends on context: the same hallway may require different navigation strategies when crowded versu…
Steering Dialogue Dynamics for Robustness against Multi-turn Jailbreaking Attacks
Hanjiang Hu, Alexander Robey, Changliu Liu
Large language models (LLMs) are shown to be vulnerable to jailbreaking attacks where adversarial prompts are designed to elicit harmful responses. While existing defenses effectiv…