AI RESEARCH
Orion-Lite: Distilling LLM Reasoning into Efficient Vision-Only Driving Models
arXiv CS.CV
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ArXi:2604.08266v1 Announce Type: new Leveraging the general world knowledge of Large Language Models (LLMs) holds significant promise for improving the ability of autonomous driving systems to handle rare and complex scenarios. While integrating LLMs into Vision-Language-Action (VLA) models has yielded state-of-the-art performance, their massive parameter counts pose severe challenges for latency-sensitive and energy-efficient deployment.