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[问与答] 自动驾驶如何应对大模型的幻觉问题的?

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关注到最近车企都在推端到端的自动驾驶大模型了,但是目前的大模型不都是生成式的么,车企如何解决大模型的幻觉问题的?在道路上的大模型,一旦输出错误的结果,就非常危险了,车企如何应对这些问题的?

我现在推测可能是预训练的小参数量、多模态模型,在端侧 orinx 推理后,再由传统的 rule-base 的模型做一层验证 or 过滤?可能以前的 rule 是道路规则,现在的 rule 可能是违规规则,以实现对大模型输出的危险的结果的过滤?

有行业内的朋友科普一下吗

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