6 papers
Affordance Field Intervention: Enabling VLAs to Escape Memory Traps in Robotic Manipulation
Siyu Xu, Zijian Wang, Yunke Wang +3
Vision-Language-Action (VLA) models have shown great performance in robotic manipulation by mapping visual observations and language instructions directly to actions. However, they…
MambaScope: Coarse-to-Fine Scoping for Efficient Vision Mamba
Shanhui Liu, Rui Xu, Yunke Wang
Vision Mamba has emerged as a promising and efficient alternative to Vision Transformers, yet its efficiency remains fundamentally constrained by the number of input tokens. Existi…
Action-aware Dynamic Pruning for Efficient Vision-Language-Action Manipulation
Xiaohuan Pei, Yuxing Chen, Siyu Xu +3
Robotic manipulation with Vision-Language-Action models requires efficient inference over long-horizon multi-modal context, where attention to dense visual tokens dominates computa…
Marine Saliency Segmenter: Object-Focused Conditional Diffusion with Region-Level Semantic Knowledge Distillation
Laibin Chang, Yunke Wang, JiaXing Huang +3
Marine Saliency Segmentation (MSS) plays a pivotal role in various vision-based marine exploration tasks. However, existing marine segmentation techniques face the dilemma of objec…
VLA-Cache: Efficient Vision-Language-Action Manipulation via Adaptive Token Caching
Siyu Xu, Yunke Wang, Chenghao Xia +3
Vision-Language-Action (VLA) models have demonstrated strong multi-modal reasoning capabilities, enabling direct action generation from visual perception and language instructions…
Position: AI Scaling: From Up to Down and Out
Yunke Wang, Yanxi Li, Chang Xu
AI Scaling has traditionally been synonymous with Scaling Up, which builds larger and more powerful models. However, the growing demand for efficiency, adaptability, and collaborat…