清華拓展受控世界模型

Computer Science > Machine Learning arXiv:2607.

22430 (cs) [Submitted on 24 Jul 2026 (v1), last revised 27 Jul 2026 (this version, v2)] Title:On the Identifiability of Controlled World Models Authors:Xiangteng Zhang, Yang Guan, Bo Zhang, Hongyang Li, Ya-Qin Zhang, Shengbo Eben Li View a PDF of the paper titled On the Identifiability of Controlled World Models, by Xiangteng Zhang and 5 other authors View PDF HTML (experimental) Abstract:World model serves as a promising tool to infer environment dynamics under high-dimensional observations and candidate actions.

Recently, LeCun's JEPA provides a compelling framework for learning such models in representation space.

Its action-conditioned extension plays a central role in visual control and latent-space planning, but leaves a fundamental question: can it recover the controlled dynamics from nonlinear observations?

This paper presents a joint identifiability condition for controlled world models with Gaussian latent states, which consists of two coupled components: (1) representation identifiability and (2) transition identifiability.

The former depends on the spectral separation property while the latter is related to non-degenerate variation of conditional action.

We prove that when this condition holds, minimizing the LeJEPA-style predictive objective can recover both latent states and controlled dynamics in the sense of orthogonal transformation.

We further prove that the upper bound of transition prediction error is inversely proportional to the spectral separation margin.We also characterize an attainable amplification of counterfactual prediction error that scales inversely with the weakest conditional action-excitation margin.

The theoretical predictions are empirically supported across four nonlinear observation settings.Subjects: Machine Learning (cs.LG) Cite as: arXiv:2607.22430 [cs.LG] (or arXiv:2607.22430v2 [cs.LG] for this version) https://doi.org/10.48550/arXiv.2607.

22430 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Xiangteng Zhang [view email] [v1] Fri, 24 Jul 2026 15:49:12 UTC (4,653 KB) [v2] Mon, 27 Jul 2026 09:57:43 UTC (4,653 KB) Full-text links: Access Paper: View a PDF of the paper titled On the Identifiability of Controlled World Models, by Xiangteng Zhang and 5 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: cs.

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