一篇新的研究论文介绍了一种在视觉-语言-动作（VLA）模型的自回归策略中实现实时执行的方法。该方法通过调整标记化范围和采用约束解码来保证严格的延迟界限。这使得多轨迹解码成为可能，从而提高了任务完成速度，并在模拟和现实世界环境中均优于等效的流匹配策略。 AI
影响 通过改进自回归策略的执行，使现实世界应用中的AI代理更快、响应更灵敏。
排序理由 该集群包含一篇详细介绍AI模型新技术方法的 ist 研究论文。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2606.13355v1 Announce Type: cross Abstract: Real-time execution, enabled by asynchronous inference that ensures both smooth action trajectories and fast reactivity, is critical for realistic deployments of large-scale Vision-Language-Action models. However, recent work on r…
Real-time execution, enabled by asynchronous inference that ensures both smooth action trajectories and fast reactivity, is critical for realistic deployments of large-scale Vision-Language-Action models. However, recent work on real-time execution primarily focuses on variants o…