Awesome Robotics Manipulation · full_paper

Breaking Lock-In: Preserving Steerability under Low-Data VLA Post-Training

作者：作者信息待提取 · 单位：Stanford University · 会议/期刊：arXiv · 日期：2026-04-25 · 来源：Low-Level Learning-Based Action Modelling / Input Modelling / 2D Vision Language Action Models for Generalization / Environment/Language Changes

视觉语言动作泛化机器人学习数据集/基准
新标签打开 AlphaXiv新标签打开 Paper新标签打开 Project
Breaking Lock-In: Preserving Steerability under Low-Data VLA Post-Training figure
AlphaXiv 中文论文页面（可滚动查看）