LeWorldModel: The Missing Structure
LeWorldModel · End-to-End World Model from Raw Pixels · Minimal Objective
Abstract LeWorldModel (2026) presents a clean, end-to-end JEPA-style world model trained from raw pixels with a minimal objective, reducing training complexity and enabling faster planning. The minimalist design philosophy — remove everything that can be removed — makes the structural gaps especially visible: when you strip away all the heuristics, the missing symbols become the only thing left to add.
6 FORMAL GAPS · 1 PER CANON SYMBOL
Minimal Objective Pixel World Model Has No Invariant Floor
γ₁ — THE FLOOR
LeWorldModel builds a world model directly from raw pixels with a minimal objective. Minimality means no added structure beyond what is necessary. But γ₁ is not added structure — it is the mathematical truth that the world model must converge to. Without an invariant floor, a minimal world model is a compressed description of the training distribution, not a model of the world.
Raw Pixel Prediction Not Self-Adjoint at Any Compression Level
H=H† — THE HONEST GATE
LeWorldModel predicts world states from raw pixels at multiple compression levels. At no compression level is the prediction formally self-adjoint: encode(pixel_state) is not verifiable against decode(encode(pixel_state)) in a symmetric way that satisfies H=H†. The pixel-level H=H† gap is the most fundamental: pixels are not self-adjoint operators.
No Paradigm Audit During End-to-End Training
LSOS — THE READER
LeWorldModel trains end-to-end: the world model, planner, and policy are jointly optimized. During end-to-end training, the paradigm of each component shifts in response to the others. There is no audit of these mutual paradigm shifts. LSOS would read the active paradigm of each component and flag when they are shifting in incompatible directions.
No Reset When Minimal World Model Collapses
WLD — THE RESET
When LeWorldModel's minimal world model collapses — when it learns to predict only the mean pixel distribution — there is no mercy reset. Minimal objectives are particularly prone to collapse: removing heuristic safeguards means the only protection against collapse is the objective itself. WLD provides the missing collapse recovery.
No Continuity Guarantee Between Fast and Slow Planning
FEP — THE SWITCH
LeWorldModel enables faster planning than foundation-model-based pipelines. The speed/quality tradeoff in planning is a paradigm switch: fast planning uses less world model capacity, slow planning uses more. There is no formal continuity guarantee for this switch. FEP ensures that the planning paradigm is preserved when switching between speed regimes.
World Model Complexity Ceiling Undefined
FOF — THE BREACH
LeWorldModel does not define a formal upper bound on world model complexity. As the world becomes more complex (more objects, more causal relationships, longer temporal horizons), the minimal objective becomes insufficient. The point where the LeWorldModel fails to model the world is not named. FOF names this boundary.
STE COMPLETION LAYER
What changes when you add the 8-symbol Canon
Adding the Canon to LeWorldModel does not change the architecture. It adds the missing structural layer:

⚓ γ₁ — invariant anchor: mathematical ground truth latent representations must converge to.
⯛ H=H† — honest gate: bidirectional verification of every prediction.
〰️ LSOS — paradigm reader: reads active paradigm before reasoning begins.
🌀 WLD — mercy reset: detects collapse and resets to last stable state.
γ FEP — safe switch: continuity guarantee across paradigm transitions.
🌌 FOF — named ceiling: formal boundary of what the architecture can claim.
═ EVEN — substrate: ground beneath all the above. What holds when everything else is active.

The Canon is not an add-on. It is the formal completion of the JEPA programme.