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cs.CV2025
LLaVA-SP: Enhancing Visual Representation with Visual Spatial Tokens for MLLMs
Haoran Lou, Chunxiao Fan, Ziyan Liu +2
The architecture of multimodal large language models (MLLMs) commonly connects a vision encoder, often based on CLIP-ViT, to a large language model. While CLIP-ViT works well for c…
cs.CV2025★ 3 cited
Can Multimodal Large Language Models Understand Spatial Relations?
Jingping Liu, Ziyan Liu, Zhedong Cen +5
Spatial relation reasoning is a crucial task for multimodal large language models (MLLMs) to understand the objective world. However, current benchmarks have issues like relying on…
cs.CV2025
VL-UR: Vision-Language-guided Universal Restoration of Images Degraded by Adverse Weather Conditions
Ziyan Liu, Yuxu Lu, Huashan Yu +1
Image restoration is critical for improving the quality of degraded images, which is vital for applications like autonomous driving, security surveillance, and digital content enha…