Mosaic uses cross-modal clusters as the unit for KVCache organization in VLMs to achieve up to 1.38x speedup in streaming long-video understanding.
Drivegpt4: Interpretable end-to-end autonomous driving via large language model
2 Pith papers cite this work, alongside 316 external citations. Polarity classification is still indexing.
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316
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A vision-language model classifies road surface and visibility conditions from front-camera images, parametrizing a context-adaptive safety envelope that couples braking and steering through a shared friction budget, achieving 100% trial success in CARLA simulation across adverse conditions.
citing papers explorer
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Mosaic: Cross-Modal Clustering for Efficient Video Understanding
Mosaic uses cross-modal clusters as the unit for KVCache organization in VLMs to achieve up to 1.38x speedup in streaming long-video understanding.
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VLM-CASE: Vision-Language Model Enabled Context-Adaptive Safety Envelopes for Anticipatory Safe Autonomous Driving
A vision-language model classifies road surface and visibility conditions from front-camera images, parametrizing a context-adaptive safety envelope that couples braking and steering through a shared friction budget, achieving 100% trial success in CARLA simulation across adverse conditions.