DUALVISION is a new lightweight fusion module using localized cross-attention to integrate infrared with RGB data in MLLMs, improving robustness to degradations and supported by the new DV-204K training dataset and DV-500 benchmark.
A survey on multimodal large lan- guage models for autonomous driving
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Saliency-R1 uses a novel saliency map technique and GRPO with human bounding-box overlap as reward to improve VLM reasoning faithfulness and interpretability.
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DUALVISION: RGB-Infrared Multimodal Large Language Models for Robust Visual Reasoning
DUALVISION is a new lightweight fusion module using localized cross-attention to integrate infrared with RGB data in MLLMs, improving robustness to degradations and supported by the new DV-204K training dataset and DV-500 benchmark.
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Saliency-R1: Enforcing Interpretable and Faithful Vision-language Reasoning via Saliency-map Alignment Reward
Saliency-R1 uses a novel saliency map technique and GRPO with human bounding-box overlap as reward to improve VLM reasoning faithfulness and interpretability.