MultiEcho：学习世界的实验科学

中文摘要 AI 辅助

世界模型可以被研究为具有自身响应规律的实验系统。我们引入了MultiEcho，一个通过受控反事实干预来估计这些规律、界定其适用范围并分别测试其物理对应性的框架。在九个模拟物理系统和七个冻结模型配置中，三参考估计器预测了完整的干预响应并恢复了干预参数。估计器的选择仅使用发现数据；冻结拟合在验证和确认情境中进行评估。实验区分了响应可预测性、干预可读性和物理准确性。响应可能在局部可描述，但在相同目标坐标下与物理效应的匹配较差。事件窗口、可见性和相机干预揭示了条件适用性，配对生成器配置在更强引导的场景提示下显示出降低的可读性。幅度扫描暴露了小的图像误差和大的相对效应误差。一个精确重置的物理实验分离了在匹配位置和速度下对物质依赖未来的注册可见响应成功与固定读数失败。精确的有限尺度恒等式解决了奇偶响应误差；一阶余项界指定了精细校准何时收敛。MultiEcho为独立于物理定律并与之相关的学习世界规律研究提供了实验基础。

英文摘要

World models can be studied as experimental systems with response laws of their own. We introduce MultiEcho, a framework for estimating these laws through controlled counterfactual interventions, delimiting their applicability, and separately testing their physical correspondence. Across nine simulated physical systems and seven frozen model configurations, three-reference estimators predict complete intervention responses and recover intervention parameters. Estimator selection uses discovery data only; frozen fits are evaluated on validation and confirmation contexts. The experiments distinguish response predictability, intervention readability and physical accuracy. Responses can be locally describable yet poorly match physical effects in the same target coordinates. Event-window, visibility and camera interventions reveal conditional applicability, and paired generator configurations show reduced readability under a scene prompt with stronger guidance. Magnitude sweeps expose small image errors alongside large relative effect errors. An exact-reset material experiment separates registered visible-response success from fixed-readout failure on material-dependent futures at matched positions and velocities. Exact finite-scale identities resolve odd and even response errors; first-order remainder bounds specify when refined calibration converges. MultiEcho provides an experimental basis for studying learned-world laws independently of, and in relation to, physical laws.

发表机构

• SHIHAO XINRUI Group（世豪鑫瑞集团）

机构由 AI 辅助整理，请以论文原文为准。