5 papers
From Indoor to Open World: Revealing the Spatial Reasoning Gap in MLLMs
Mingrui Wu, Zhaozhi Wang, Fangjinhua Wang +3
While Multimodal Large Language Models (MLLMs) have achieved impressive performance on semantic tasks, their spatial intelligence--crucial for robust and grounded AI systems--remai…
VideoAnchor: Reinforcing Subspace-Structured Visual Cues for Coherent Visual-Spatial Reasoning
Zhaozhi Wang, Tong Zhang, Mingyue Guo +2
Multimodal Large Language Models (MLLMs) have achieved impressive progress in vision-language alignment, yet they remain limited in visual-spatial reasoning. We first identify that…
RS-vHeat: Heat Conduction Guided Efficient Remote Sensing Foundation Model
Huiyang Hu, Peijin Wang, Hanbo Bi +10
Remote sensing foundation models largely break away from the traditional paradigm of designing task-specific models, offering greater scalability across multiple tasks. However, th…
Building Vision Models upon Heat Conduction
Zhaozhi Wang, Yue Liu, Yunjie Tian +3
Visual representation models leveraging attention mechanisms are challenged by significant computational overhead, particularly when pursuing large receptive fields. In this study,…
Mixture of Physical Priors Adapter for Parameter-Efficient Fine-Tuning
Zhaozhi Wang, Conghu Li, Qixiang Ye +1
Most parameter-efficient fine-tuning (PEFT) methods rely on low-rank representations to adapt models. However, these approaches often oversimplify representations, particularly whe…