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  • [2601. 21998] Causal World Modeling for Robot Control - arXiv. org
    We evaluate our model on both simulation benchmarks and real-world scenarios, where it shows significant promise in long-horizon manipulation, data efficiency in post-training, and strong generalizability to novel configurations
  • LingBot-VA: Causal World Modeling for Robot Control - GitHub
    LingBot-VA supports both standalone execution and Server-Client architecture which separates the model environment from simulation By isolating dependencies, the design avoids package clashes and supports distributed inference on GPUs, clusters, and other devices
  • 【论文阅读】LingBot-VA:Causal World Modeling for Robot . . .
    世界模型的“非因果”问题：现有的视频世界模型多采用双向注意力机制（能看到未来也能看到过去），这不符合物理世界“过去决定现在”的因果逻辑，导致在实际闭环控制中容易产生误差累积和漂移。 实时性难题：生成视频通常计算量大，难满足机器人控制的高频率实时性要求。 提出了 LingBot-VA，一个自回归扩散世界模型。 核心是将视频帧和动作 token 交织在一起，通过单向因果掩码进行预测，并设计了异步推理pipeline，在机器人执行当前动作时后台预测下一时刻的画面与动作。 要实现通用机器人控制，不能仅靠模仿学习（反应式），必须让机器人学会“想象”未来的视觉画面。
  • 用于机器人控制的因果世界建模 - 知乎
    26年1月来自蚂蚁Robbyant的论文“Causal World Modeling for Robot Control”。 这项工作强调，视频世界建模与视觉语言预训练相结合，为机器人学习建立一个全新且独立的基础。 直观地说，视频世界模型能够通过理解动作和视觉动态之间的因果关系来“想象”近期
  • Causal World Modeling for Robot Control - emergentmind. com
    This paper introduces a causal world modeling framework that integrates video prediction and action control for robust and efficient robotic manipulation
  • Causal World Modeling for Robot Control - Semantic Scholar
    We evaluate our model on both simulation benchmarks and real-world scenarios, where it shows significant promise in long-horizon manipulation, data efficiency in post-training, and strong generalizability to novel configurations
  • Paper page - Causal World Modeling for Robot Control
    Our model features three carefully crafted designs: (1) a shared latent space, integrating vision and action tokens, driven by a Mixture-of-Transformers (MoT) architecture, (2) a closed-loop rollout mechanism, allowing for ongoing acquisition of environmental feedback with ground-truth observations, (3) an asynchronous inference pipeline, parall
  • Causal World Modeling for Robot Control - alphaXiv
    By overlapping computation with execution and incorporating environmental feedback loops, the system demonstrates how sophisticated world models can operate within the timing constraints of real-time robotic control





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