5 papers
REKI: Registering Knowledge in VLAs
Juliette Marrie, Paul Pacaud, Adrien Ramanana Rahary +2
We introduce REKI, a 2.4B vision-language-action model (VLA) pretrained exclusively on public data that sets a new Pareto frontier between performance and model size: on LIBERO-Plu…
Spatially Aware World Action Model via Geometric Latent Diffusion
Javier Alejandro Lopetegui Gonzalez, Paul Pacaud, Cordelia Schmid
World Action Models (WAMs) leverage the capabilities of large-scale pretrained video diffusion models to jointly predict future observations and actions, inheriting rich visual and…
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…
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…
Gondola: Grounded Vision Language Planning for Robotic Manipulation
Shizhe Chen, Ricardo Garcia, Paul Pacaud +1
Vision-language-action (VLA) models have shown promising progress in robotic manipulation. However, directly mapping visual observations and language instructions to low-level acti…