OpenVLA框架

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保持精度,提升速度!Spec-VLA:首个专为VLA推理加速设计的推测解码框架
具身智能之心· 2025-08-14 00:03
Core Viewpoint - The article discusses the introduction of the Spec-VLA framework, which utilizes speculative decoding to accelerate the inference process of Vision-Language-Action (VLA) models, achieving significant speed improvements without the need for fine-tuning the VLA validation model [2][6]. Group 1: Spec-VLA Framework - Spec-VLA is the first speculative decoding framework specifically designed for accelerating VLA inference [2]. - The framework demonstrates a 42% acceleration compared to the OpenVLA baseline model, achieved by training only the draft model [6]. - The proposed mechanism enhances the acceptance length by 44% while maintaining the task success rate [2]. Group 2: Technical Details - The article highlights the challenges posed by the large parameter scale and autoregressive decoding characteristics of Vision-Language Models (VLMs) [2]. - Speculative decoding (SD) allows large language models (LLMs) to generate multiple tokens in a single forward pass, effectively speeding up inference [2]. - The framework employs a relaxed acceptance mechanism based on the relative distances represented by action tokens in VLA models [2]. Group 3: Live Broadcast Insights - The live broadcast covers key topics such as speculative decoding as an acceleration method for large language models, an introduction to VLA models, and detailed implementation aspects of the Spec-VLA framework [7].