Motus: A Unified Latent Action World Model

This article introduces Motus, a research paper from ArXiv. The title suggests a focus on a unified model for understanding and predicting actions within a latent space, likely related to reinforcement learning or embodied AI. The use of "latent" implies the model operates on a hidden representation of the world, potentially simplifying complex action spaces. Further analysis would require reading the paper itself to understand the specific architecture, training methods, and performance.