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CoRE reveals that coarse video predictions can effectively guide the identification of fine-grained risk evidence, eliminating the need for detailed annotations.
Even slight variations in natural language instructions can cause language-driven autonomous driving models to fail dramatically, revealing a critical reliability gap for real-world deployment.
