3 citations · 7 across the 13 of their papers we have counts for
9 papers · 1 filter
The Memory Trap: Language Agents Overgeneralize from Benign Interactions
Kaiqu Liang, Jaime Fernández Fisac, Thomas L. Griffiths +1
Language agents increasingly use persistent memory to record user preferences and procedures across sessions. We show that memory from benign interactions can cause unsafe or unrel…
Confidence-Modulated Safety Filtering for End-to-End Policies
Javier Borquez, Jaime F. Fisac
End-to-end policies, from task-specific controllers to robot foundation models, learn complex behavior from raw observations but are not guaranteed to remain safe, so they are ofte…
Training Controllable World Models via Action Influence Maximization
Samuel M. Bateman, Tenny Yin, Chongyi Zheng +5
Action-conditioned video generative models trained on successful, goal-directed demonstrations tend to ignore the commanded action, rendering a plausible expert-like future regardl…
Winning a Won Game: Strict Reach-Avoid-Stay Control Barrier Functions for High-Dimensional Black-Box Systems
Donggeon David Oh, Duy P. Nguyen, Gongkai Yuan +3
Robots must complete their tasks and maintain the achieved outcomes while avoiding safety failures at all times. Strict reach-avoid-stay (sRAS) formalizes this requirement: safely…
Corrigible Assistance in One Round: Pragmatic-Pedagogic Best Response
Elle Lazarski, Jaime Fernández Fisac
Assistance games formalize human-robot collaboration under asymmetric information: the human knows the goal, while the robot must infer it from observation and interaction in order…
Human-like autonomy emerges from self-play and a pinch of human data
Daphne Cornelisse, Julian Hunt, Zixu Zhang +4
Self-play reinforcement learning has recently emerged as a way to train driving policies without any human data. It uses cheap, large-scale simulations to substitute expensive, lar…
Synthesis and Deployment of Maximal Robust Control Barrier Functions through Adversarial Reinforcement Learning
Donggeon David Oh, Duy P. Nguyen, Haimin Hu +1
Robust control barrier functions (CBFs) provide a principled mechanism for smooth safety enforcement under worst-case disturbances. However, existing approaches typically rely on e…
Learning Personalized Agents from Human Feedback
Kaiqu Liang, Julia Kruk, Shengyi Qian +9
Modern AI agents are powerful but often fail to align with the idiosyncratic, evolving preferences of individual users. Prior approaches typically rely on static datasets, either t…
Robotic Video World Models: A Survey of Applications, Research Challenges, Future Directions
Zhiting Mei, Tenny Yin, Ola Shorinwa +9
Video world models have emerged as promising candidates for high-fidelity world models, offering the potential to synthesize high-quality videos capturing fine-grained interactions…