AIBullisharXiv – CS AI · 9h ago7/10
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Drive-KD: Multi-Teacher Distillation for VLMs in Autonomous Driving
Researchers introduce Drive-KD, a knowledge distillation framework that compresses large vision-language models for autonomous driving by decomposing the task into perception, reasoning, and planning components. The method achieves superior performance with 42x less GPU memory and 11.4x higher throughput compared to larger baseline models, advancing the practical deployment of AI in safety-critical driving systems.
🧠 GPT-5