arXiv cs.AI· Rodrigo Gonzalez Laiz, Steffen Schneider·· 13 小时前AI 评分42
研究揭示潜在世界模型的局限：现有SOTA模型均未忠实建模环境动态
Understanding the limits of latent world models
AI 导读
研究提出"忠实潜在世界模型"概念，将其定义为环境转移映射与学习到的潜在动态之间的等变性条件，并给出评估动作条件潜在预测的指标 latent rollout consistency（LRC）。在所研究的当前SOTA潜在世界模型中，没有一个模型是通过真正忠实建模环境动态来完成任务的。
正文 · 原文
Abstract:World models are widely proposed as core components for enabling agents to reason over long temporal and spatial horizons. Yet current evaluations often emphasize task performance while providing limited insight into whether learned world models acquire predictive latent dynamics that reflect the underlying structure of the environment. Here we introduce the concept of faithful latent world models as an equivariance condition between the environment's transition map and the learned latent dynamics. We propose latent rollout consistency (LRC) as a metric to evaluate action-conditioned latent prediction. Strikingly, we find that across the studied state of the art latent world models, none solves the task by actually faithfully modeling the dynamics of the environment.
| Subjects: | Machine Learning (cs.LG); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.37588 [cs.LG] |
| (or arXiv:2610.37588v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2610.37588 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Rodrigo Gonzalez Laiz [view email]
[v1]
Tue, 27 Oct 2026 17:25:50 UTC (17,985 KB)
来源：arXiv cs.AI · arxiv.org