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cs.AI2026
ADAPT: Audio-Depth Action Planning with Transition-Aware Rewards for Lights-Out Industrial Navigation
Wenjun Huang, Shenghao Fu, Yian Jin +12
Vision-language-action models for embodied navigation typically rely on RGB observations, limiting their applicability in lights-out industrial environments where visible illuminat…
cs.CV2026
PixelDense: Dense Prediction as Representation Alignment for Pixel Diffusion
Lehan Yang, Daiqing Qi, Wenhao Zhang +9
Representation alignment (REPA) accelerates diffusion transformer training, but its alignment targets are almost exclusively semantic encoders such as DINOv2 and CLIP. Recent analy…
cs.CV2026
ViT-AdaLA: Adapting Vision Transformers with Linear Attention
Yifan Li, Seunghyun Yoon, Viet Dac Lai +4
Vision Transformers (ViTs) based vision foundation models (VFMs) have achieved remarkable performance across diverse vision tasks, but suffer from quadratic complexity that limits…