VLA-Pilot：无需微调即可部署的VLA策略引导框架

Core Insights - The article discusses the VLA-Pilot framework, which allows for zero-shot deployment of pre-trained VLA strategies without the need for fine-tuning or additional data collection, addressing the high costs associated with demonstration data and computational resources [2][6]. Group 1: VLA-Pilot Framework - VLA-Pilot is a plug-and-play inference-time policy steering method that significantly enhances the success rate of existing pre-trained VLA strategies across various tasks and robot entities [2][6]. - The framework has been evaluated on six real-world downstream operational tasks, demonstrating robust zero-shot generalization capabilities [2][6]. Group 2: Challenges and Solutions - Pre-trained VLA strategies experience a notable performance drop during downstream deployment, which can be mitigated through fine-tuning, but this approach is limited by high data and resource requirements [2][6]. - The VLA-Pilot framework provides a data-efficient solution that eliminates the need for fine-tuning, making it more applicable in real-world scenarios [6]. Group 3: Live Event Details - A live session is scheduled for December 9, from 19:30 to 20:30, to discuss the VLA-Pilot framework and its implications [6]. - The session will cover the introduction of VLA models, the VLA-Pilot framework, and its implementation details [7].