摘要：本文提出RoboTTT方法，通过将测试时训练（TTT）机制整合到机器人基础模型中，实现了8K时间步的长视觉-运动上下文建模。该方法采用快速权重机制，在训练和推理时动态更新模型参数，将历史信息压缩至权重空间，解决了长上下文建模的三大挑战。实验表明，RoboTTT-8K相比单步基线在复杂任务中性能提升87%，首次证明扩展上下文长度能稳定提升闭环性能（比1K上下文模型提升63%）。创新性地结...

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