2 papers
cs.AI2026
MemWM: Memory-Augmented Text-Based World Model
Yujun Wang, Tao Zhang, Jinhe Bi +9
World models are increasingly used to support planning in agents by predicting how environment states evolve in response to agent actions. Yet fluent next-state predictions can sti…
cs.RO2026
HUMEMBR: Learning Human Routines for Predictive Embodied Navigation
Samira Huber, Klaas Pelzer, Duc M. Nguyen +2
Understanding and navigating human-centered environments over extended periods of time while considering human behavior and routines remains a fundamental challenge in robotics. In…