A platform for reproducible world model research and evaluation
RSI-Anything: Unlocking Recursive Self-Improvement with World Models
[ECCV 2026] VLA-JEPA: Enhancing Vision-Language-Action Model with Latent World Model
JEPA-Anything: Learning Predictive Models across Different Worlds
A small proof-of-concept language model (not an LLM) that aims to incorporate latent-space prediction, internal state using recurrent trace units, and byte-by-byte output, built with MLX.
Efficient & Scalable Video Pretraining without the Heuristics
INTACT: Isomorphic Intent-to-Action Learning for Search-Free World Models.
Free interactive course on world models in AI. Nine visual chapters on prediction, latent dynamics, planning, JEPA, video models, and failure modes.
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First JEPA-based learning framework for mapping-free LiDAR-based perceptive locomotion
WA-JEPA: Rethinking the Video JEPA Paradigm for World-Action Modeling in Autonomous Driving
AD-E2E-JEPA: A Joint-Embedding Predictive Architecture For End-to-End Autonomous Driving
OSS of roboJEPA
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InJepa: Intention First Latent State Planning with Coupled JEPAs for Visual Navigation. Code, Clean150 tasks and E12 checkpoint.
Official Code for LpWM: A Case for Sparse Representations in World Models
D-JEPA: A Decision-Aligned Latent World Model
Build world models from scratch β from perception and latent dynamics to planning, JEPA, VLA, and 3D/4D intelligence.