WCog-VLA couples Game-CoT semantic reasoning with an aligned decoupled diffusion transformer to generate joint multi-agent trajectories and reaches 92.9 PDMS on NAVSIM.
IEEE Robotics and Automation Letters11(1), 226–233 (2025)
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
baseline 1
citation-polarity summary
fields
cs.CV 2years
2026 2roles
baseline 1polarities
baseline 1representative citing papers
Dense future RGB/depth world modeling both supervises a VLA planner and supplies safety-gated uncertainty rewards that, optimized with GRPO, reach 93.7 PDMS on NAVSIM.
citing papers explorer
-
WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving
WCog-VLA couples Game-CoT semantic reasoning with an aligned decoupled diffusion transformer to generate joint multi-agent trajectories and reaches 92.9 PDMS on NAVSIM.
-
ExploreVLA: Dense World Modeling and Exploration for End-to-End Autonomous Driving
Dense future RGB/depth world modeling both supervises a VLA planner and supplies safety-gated uncertainty rewards that, optimized with GRPO, reach 93.7 PDMS on NAVSIM.