Fine-tuning multimodal language models on a new SOTIF-focused driving dataset improves question answering and captioning, but the open-ended gains are measured by an LLM judge with no independent human scoring.
A holistic robust motion control framework for autonomous platooning,
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DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models
Fine-tuning multimodal language models on a new SOTIF-focused driving dataset improves question answering and captioning, but the open-ended gains are measured by an LLM judge with no independent human scoring.