10 papers
MuRA: Multi-Rank Adaptation for Efficient and Effective Test-Time Vision-Language Generalization
Gengyuan Liu, Nanzhou Wang, Chang Liu +5
Vision-language models exhibit remarkable zero-shot capabilities but suffer significant performance degradation under distribution shifts. While test-time adaptation (TTA) via Low-…
SAMTok: Representing Any Mask with Two Words
Yikang Zhou, Tao Zhang, Dengxian Gong +13
Pixel-wise capabilities are essential for building interactive intelligent systems. However, pixel-wise multi-modal LLMs (MLLMs) remain difficult to scale due to complex region-lev…
AutoPDE: Reliable Agentic PDE Solving via Explicitly Represented Solver Strategies
Huanshuo Dong, Keyao Zhang, Hong Wang +6
Numerical solvers for partial differential equations (PDEs) are core computational tools in science and engineering. Building reliable PDE solvers requires not only executable code…
Grasp Any Region: Towards Precise, Contextual Pixel Understanding for Multimodal LLMs
Haochen Wang, Yuhao Wang, Tao Zhang +13
While Multimodal Large Language Models (MLLMs) excel at holistic understanding, they struggle in capturing the dense world with complex scenes, requiring fine-grained analysis of i…
Traceable Evidence Enhanced Visual Grounded Reasoning: Evaluation and Methodology
Haochen Wang, Xiangtai Li, Zilong Huang +9
Models like OpenAI-o3 pioneer visual grounded reasoning by dynamically referencing visual regions, just like human "thinking with images". However, no benchmark exists to evaluate…
Fusing Pixels and Genes: Spatially-Aware Learning in Computational Pathology
Minghao Han, Dingkang Yang, Linhao Qu +5
Recent years have witnessed remarkable progress in multimodal learning within computational pathology. Existing models primarily rely on vision and language modalities; however, la…