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.
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3 Pith papers cite this work. Polarity classification is still indexing.
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RosettaSim adapts frozen LLMs via structured autoregressive modeling of scene topology and agent states to reach SOTA short- and long-term traffic simulation on WOSAC, paired with RTE evaluation that correlates better with human-like fidelity.
LACO introduces Iterative Latent Deliberation, Cross-Horizon Saliency Attribution, and Structured Semantic Knowledge Distillation to enable low-latency latent communication in collaborative driving while preserving performance in CARLA simulations.
citing papers explorer
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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.
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Long-term Traffic Simulation via Structured Autoregressive Modeling
RosettaSim adapts frozen LLMs via structured autoregressive modeling of scene topology and agent states to reach SOTA short- and long-term traffic simulation on WOSAC, paired with RTE evaluation that correlates better with human-like fidelity.
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LACO: Adaptive Latent Communication for Collaborative Driving
LACO introduces Iterative Latent Deliberation, Cross-Horizon Saliency Attribution, and Structured Semantic Knowledge Distillation to enable low-latency latent communication in collaborative driving while preserving performance in CARLA simulations.