What exactly does LeCun's 2022 position paper propose as the world model module (JEPA, H-JEPA), and which parts are untested in that document?

Version 0.9.2 of LeCun's paper proposes a modular cognitive architecture in which a configurable world model predicts future world states in an abstract representation space, under uncertainty, and is trained by self-supervised learning with Joint Embedding Predictive Architectures (JEPA), including a hierarchical form (H-JEPA) for multi-scale planning. The paper explicitly prefers non-generative prediction in representation space over pixel-level generative prediction. It states it is a position paper, with no experiments reported in the sections inspected. Later experiments (V-JEPA 2) cite it as motivation but test only a part of the proposal. Curator qualifications: Capture text: 'Version 0.9.2, 2022-06-27'; 'This position paper proposes an architecture and training paradigms'; Prologue: 'This document is not a technical nor scholarly paper in the traditional sense, but a position paper'; 'JEPA and Hierarchical JEPA: a non-generative architecture for predictive world models'; 'The JEPA is non-generative in that it does not actually predict y, but predicts the representation of y'. 'JEPA' 53 lines. Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

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      "url": "https://openreview.net/pdf?id=BZ5a1r-kVsf",
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    {
      "url": "https://arxiv.org/abs/2506.09985v1",
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