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cs.LG2026
IPD: Boosting Sequential Policy with Imaginary Planning Distillation in Offline Reinforcement Learning
Yihao Qin, Yuanfei Wang, Hang Zhou +3
Decision transformer based sequential policies have emerged as a powerful paradigm in offline reinforcement learning (RL), yet their efficacy remains constrained by the quality of…
cs.RO2026
Physics-informed Diffusion Mamba Transformer for Real-world Driving
Hang Zhou, Qiang Zhang, Peiran Liu +3
Autonomous driving systems demand trajectory planners that not only model the inherent uncertainty of future motions but also respect complex temporal dependencies and underlying p…