SOURCE-LINKED INTELLIGENCE

AdaVLA: Adaptive Step Flow Matching for Training-free Acceleration of Vision-Language-Action Models

arXiv · AI, language, vision and robotics · article · Aug 29, 2026 · UTC

Vision-Language-Action (VLA) models, built upon Vision-Language Models (VLMs), have significantly enhanced robotic capabilities by leveraging internet-scale knowledge and multimodal reasoning. However, the intensive computational overhead of VLAs constrains on-device deployment, hindering real-time responses to environmental changes. While various acceleration techniques have been proposed, they often rely on fine-tuning or access to training datasets, which are frequently unavailable due to privacy and proprietary concerns. Moreover, although flow-matching-based VLAs have emerged as efficient

Read original source ↗ Open in workspace

recordType

paper

region

Global