3 papers
cs.RO2026
PointACT: Vision-Language-Action Models with Multi-Scale Point-Action Interaction
Shizhe Chen, Paul Pacaud, Cordelia Schmid
Vision-Language-Action (VLA) models have shown strong potential for general-purpose robotic manipulation by leveraging large pretrained vision-language backbones. However, most exi…
cs.RO2026
Guardian: Detecting Robotic Planning and Execution Errors with Vision-Language Models
Paul Pacaud, Ricardo Garcia, Shizhe Chen +1
Robust robotic manipulation requires reliable failure detection and recovery. Although recent Vision-Language Models (VLMs) show promise in robot failure detection, their generaliz…
cs.RO2025
Gondola: Grounded Vision Language Planning for Generalizable Robotic Manipulation
Shizhe Chen, Ricardo Garcia, Paul Pacaud +1
Robotic manipulation faces a significant challenge in generalizing across unseen objects, environments and tasks specified by diverse language instructions. To improve generalizati…