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cs.CV2026
ProtoLIP: From Sentence-Level to Object-Level Evidence Disentanglement
Yan Zhu, Yongbo Chen, Zhengming Ding +1
Query-conditioned vision-language models enable fine-grained interpretation by revealing which visual content supports a given textual query and how this evidence changes across qu…
cs.CV2026★ 1 cited
MixerCSeg: An Efficient Mixer Architecture for Crack Segmentation via Decoupled Mamba Attention
Zilong Zhao, Zhengming Ding, Pei Niu +2
Feature encoders play a key role in pixel-level crack segmentation by shaping the representation of fine textures and thin structures. Existing CNN-, Transformer-, and Mamba-based…
cs.CV2026
Seeing Clearly, Reasoning Confidently: Plug-and-Play Remedies for Vision Language Model Blindness
Xin Hu, Haomiao Ni, Yunbei Zhang +3
Vision language models (VLMs) have achieved remarkable success in broad visual understanding, yet they remain challenged by object-centric reasoning on rare objects due to the scar…