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Research questionHow can vision-language models ground semantic driving inputs in physically plausible continuous actions with low latency?Vision-language models reason in discrete semantic representations, while vehicle control requires continuous actions constrained by vehicle dynamics. Bridging these representations without introducing trajectory errors or slow sequential generation is difficult.
AI
Evaluation & Benchmarks
Inference Optimization
Multimodal Models
Robotics
Latest papersRecent research connected to this question, newest first.Continuous Actions from Discrete Minds: Latent-Aligned Planning for End-to-End Autonomous DrivingThe source considers multi-view images, historical actions, and textual instructions as inputs, with continuous driving actions decoded through a learned vehicle-kinematics representation. Evidence comes from open-loop nuScenes experiments and closed-loop NVIDIA AlpaSim simulation; no real-world deployment evidence is provided.research paper · Sep 3, 2026
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