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cs.RO2026
Directional Pullback Regularization for Long-Horizon Rollout of Latent World Models in Autonomous Driving
Shatadal Mishra, Ahmadreza Moradipari, Nejib Ammar
Learned world models for autonomous driving operate in unconstrained latent spaces, yet the physical systems they represent are governed by strict non-holonomic constraints: ground…
cs.RO2026
Network-Efficient World Model Token Streaming
Shatadal Mishra, Ahmadreza Moradipari, Nejib Ammar
Generative driving world models rely on compact latent state representations that must be efficiently transmitted and synchronized across distributed compute and connected vehicles…
cs.RO2025
IN-RIL: Interleaved Reinforcement and Imitation Learning for Policy Fine-Tuning
Dechen Gao, Hang Wang, Hanchu Zhou +5
Imitation learning (IL) and reinforcement learning (RL) each offer distinct advantages for robotics policy learning: IL provides stable learning from demonstrations, and RL promote…