arXiv Computer Vision
Angular Supervision for Visual Object Grounding in Autoregressive Vision-Language Models
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Sa2VA: Marrying SAM2 with MLLM for Dense Grounded Understanding of Images and Videos
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0.5%>100%: Bidirectional Reciprocal Learning for Referring Image Segmentation
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When Vision Becomes Text: Visual Token Pruning via Cross-Modal Residual Guidance in VLMs
Abundant visual information strengthens vision-language model (VLM) perception, yet massive visual tokens raise inference costs. Existing visual token pruning methods rely on similarity-based guidance, which exploits pairwise text-vision and vision-vision token correlations for compression.
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Vision-Language Grounding as Bidirectional Concept Correspondence
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