1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2026
OddGridBench: Exposing the Lack of Fine-Grained Visual Discrepancy Sensitivity in Multimodal Large Language Models
Tengjin Weng, Wenhao Jiang, Jingyi Wang +3
Multimodal large language models (MLLMs) have achieved remarkable performance across a wide range of vision language tasks. However, their ability in low-level visual perception, p…
cs.CV2025★ 1 cited
UniViTAR: Unified Vision Transformer with Native Resolution
Limeng Qiao, Yiyang Gan, Bairui Wang +4
Conventional Vision Transformer simplifies visual modeling by standardizing input resolutions, often disregarding the variability of natural visual data and compromising spatial-co…