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DriveMind: Mind-Evolving Belief Tracking for Closed-Loop Autonomous Driving
Recent multimodal large language models (MLLMs) can perceive a traffic scene, reason about it, and propose a driving action within a single model. However, existing MLLM-based drivers reason from scratch at each frame and commit to a single explanation, discarding earlier hypotheses about the scene.
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