研究人员开发了一个名为ASSCG的新系统，用于优化大型语言模型（LLM）在自动驾驶规划中的使用。ASSCG充当守门员，做出帧级决策来刷新、重用或抑制慢速LLM的指导，从而降低计算成本并提高效率。当应用于现有的快慢规划架构时，ASSCG在性能指标和推理延迟降低方面均表现出显著的改进。 AI
影响 优化了自动驾驶的LLM推理，可能降低成本并改善实时决策。
排序理由 该集群描述了一篇研究论文，详细介绍了一种优化LLM在自动驾驶中使用的א新方法。
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arXiv:2606.25509v1 Announce Type: cross Abstract: Large language models (LLMs) can improve autonomous driving planning but are costly to query online, and existing fast-slow planners often rely on hand-designed triggering rules that either over-call the slow system or call it at …
Large language models (LLMs) can improve autonomous driving planning but are costly to query online, and existing fast-slow planners often rely on hand-designed triggering rules that either over-call the slow system or call it at the wrong times. We formulate slow-system invocati…