This paper aims to reduce latency and the dynamic memory usage of the π 0.5 model by performing timestep distillation on the diffusion process in the π 0.5 action head to create a 3-step diffusion action head.
Vision-Language-Action (VLA) models have become a prominent paradigm for mapping multimodal inputs, including semantic instructions, visual observations of the scene, and proprioceptive observations, to robot actions. Most state-of-the-art models predict actions in the end-effector pose space as sequences of action chu...
Mathilde Kappel, Clémence Grislain, Mohamed Chetouani et al.· 0 citations
Vision-language-action (VLA) models let robots follow language instructions, but their language backbones of several billion parameters are the main obstacle to running them on robot hardware. Structured pruning reduces that backbone, and removing 63% of it from OpenVLA-OFT drops LIBERO-Long success from 93.2% to 0.8%....
TemporalFlow-VLA provides a compact, physically grounded interface for exploiting ordered execution history without explicit motion estimation or geometric processing at deployment, and shows its clearest advantage over prior methods on longer-horizon, multi-stage manipulation.
Jia-Rui Yang, Ye-Hao Lu, Yu-Ning Su et al.· 1 citation
Reinforcement learning fine-tuning on top of large, pretrained Vision-Language-Action (VLA) models offers promise for highly reliable robot deployment. However, because of their scale, modern VLA models suffer from high inference latency, so the observation used to select an action is often stale by execution time, cre...
Perry Dong, Kuo-Han Hung, D. Sadigh et al.· 0 citations
Vision-Language-Action (VLA) models show high robotic manipulation capabilities via a two-stage design: a Vision-Language Model (VLM) stage followed by an Action Diffusion Transformer (ADiT) stage. Since robots must meet strict Service-Level Objectives (SLOs) for safety, VLA inference is inherently latency-critical. Me...
Dionysios Adamopoulos, Nattapol Chanpaisit, Basel Fakhri et al.· 0 citations
Adapting robots to new objects and tasks requires interaction experience that can be costly to obtain. We present WorldContact, a contact-centric world model for deformable-object manipulation, constructed from a limited set of high-quality trajectories to generate additional training data efficiently. It predicts obje...
Caoliwen Wang, Meng-Di Wang, Heng Zhang et al.· 0 citations
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