13 papers · 1 filter
Sparse Autoencoders Reveal Interpretable and Steerable Features in VLA Models
Aiden Swann, Lachlain McGranahan, Hugo Buurmeijer +2
Vision-Language-Action (VLA) models have emerged as a promising approach for general-purpose robot manipulation. However, little research has mechanistically explored when and why…
DOT-Sim: Differentiable Optical Tactile Simulation with Precise Real-to-Sim Physical Calibration
Yang You, Won Kyung Do, Aiden Swann +3
Simulating optical tactile sensors presents significant challenges due to their high deformability and intricate optical properties. To address these issues and enable a physically…
, But Make It Fly: Physics-Guided Transfer of VLA Models to Aerial Manipulation
Johnathan Tucker, Denis Liu, Aiden Swann +7
Vision-Language-Action (VLA) models such as have demonstrated remarkable generalization across diverse fixed-base manipulators. However, transferring these foundation models…
Phys2Real: Fusing VLM Priors with Interactive Online Adaptation for Uncertainty-Aware Sim-to-Real Manipulation
Maggie Wang, Stephen Tian, Aiden Swann +3
Learning robotic manipulation policies directly in the real world can be expensive and time-consuming. While reinforcement learning (RL) policies trained in simulation present a sc…
Observing and Controlling Features in Vision-Language-Action Models
Hugo Buurmeijer, Carmen Amo Alonso, Aiden Swann +1
Vision-Language-Action Models (VLAs) have shown remarkable progress towards embodied intelligence. While their architecture partially resembles that of Large Language Models (LLMs)…
Semantic-Metric Bayesian Risk Fields: Learning Robot Safety from Human Videos with a VLM Prior
Timothy Chen, Marcus Dominguez-Kuhne, Aiden Swann +2
Humans interpret safety not as a binary signal but as a continuous, context- and spatially-dependent notion of risk. While risk is subjective, humans form rational mental models th…