type: user

role: user

content:
Research the LeWM (LeWorldModel) paper from https://le-wm.github.io/ — I need the specific architecture details:
1. What is the exact JEPA predictor architecture? (transformer? MLP? how many layers?)
2. What is the exact next-embedding prediction loss formulation?
3. What is the exact Gaussian regularizer loss formulation?
4. How are embeddings structured (dimensions, etc)?
5. Any code available on GitHub?

Search for the paper, the GitHub repo (likely github.com/le-wm or similar), and any available code. I need implementation-level details, not just high-level concepts. Do NOT write any code — just research and report back.

userType: external

entrypoint: cli

gitBranch: HEAD

slug: valiant-watching-thunder


type: assistant

model: <synthetic>

role: assistant

type: message

type: text

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