VIP evolves text prompts using visual cues and saliency-aware aggregation inside dino.txt to deliver 1.4-8.4% higher mIoU on dense vision-language tasks with low overhead.
Adapting vision-language models without labels: A comprehensive survey.arXiv preprint arXiv:2508.05547
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VIP: Visual-guided Prompt Evolution for Efficient Dense Vision-Language Inference
VIP evolves text prompts using visual cues and saliency-aware aggregation inside dino.txt to deliver 1.4-8.4% higher mIoU on dense vision-language tasks with low overhead.