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Tag: #autonomous-driving736 results

VLM-Enhanced RL for Autonomous Driving

VLM-Enhanced RL for Autonomous Driving

Found-RL integrates foundation models into RL for end-to-end driving via async batch inference to cut latency. Distills VLM guidance using VMR, AWAG; CLIP rewards shaped by conditional alignment. Lightweight policy matches VLM perf at 500 FPS.

ArXiv AIResearchFeb 12#research#found-rl#v1
Adversarial Threat Detection in Autonomous Driving

Adversarial Threat Detection in Autonomous Driving

AD² analyzes vulnerabilities in end-to-end driving agents like Transfuser to physics, EMI, and digital attacks in CARLA. Driving scores drop up to 99% under threats. Proposes lightweight attention-based detector for spatial-temporal consistency.

ArXiv AIResearchFeb 12#research#ad2#v1
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