A researcher preparing a first arXiv submission in cs.LG is seeking an endorsement for a study introducing a random-abstractor control to test hierarchical world models (H-JEPA), finding that only par…
A developer trained a Joint-Embedding Predictive Architecture (JEPA) world model, called LeMario, on Super Mario Bros from scratch, finding the model could predict five-step futures and perform reward…
Researchers introduced Physics-Grounded Symbolic Architecture (PGSA), a new AI model that achieves exact linear identifiability across all physical regimes, overcoming the Gaussian limitation of Joint…
Algorithmic progress in AI is accelerating, with up to ten orders of magnitude in intelligence output per unit of scale still possible, signaling an early takeoff where AI improves AI. Compute and res…
A 2026 paper by Goldfeder, Wyder, LeCun, and Shwartz-Ziv argues that specialization is inevitable for AI systems, drawing on optimization theory, evolutionary biology, and machine learning. The author…
A global pause on advanced AI development is unlikely to happen before superintelligent AI (ASI) emerges, argues a commentator, because ASI risk is abstract and hard to demonstrate, unlike nuclear wea…
Researchers at arXiv propose a hybrid pre-training objective for language models that combines a Joint Embedding Predictive Architecture (JEPA) latent-space prediction loss with masked language modell…