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Jan Hünermann

2 accepted papers

2024

Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving

ICRA 2024poster

Large Language Models (LLMs) have shown promise in the autonomous driving sector, particularly in generalization and interpretability. We introduce a unique objectlevel multimodal LLM architecture that merges vectorized numeric modalities with a pre-trained LLM to improve context understanding in dr…

Cited by 229SourcecodeScholar
2024

LingoQA: Video Question Answering for Autonomous Driving

ECCV 2024poster

"We introduce LingoQA, a novel dataset and benchmark for visual question answering in autonomous driving. The dataset contains 28K unique short video scenarios, and 419K annotations. Evaluating state-of-the-art vision-language models on our benchmark shows that their performance is below human capab…