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cs.CV2025
VER-Bench: Evaluating MLLMs on Reasoning with Fine-Grained Visual Evidence
Chenhui Qiang, Zhaoyang Wei, Xumeng Han +5
With the rapid development of MLLMs, evaluating their visual capabilities has become increasingly crucial. Current benchmarks primarily fall into two main types: basic perception b…
cs.CV2024
Towards Interactive Global Geolocation Assistant
Zhiyang Dou, Zipeng Wang, Xumeng Han +3
Global geolocation, which seeks to predict the geographical location of images captured anywhere in the world, is one of the most challenging tasks in the field of computer vision.…
cs.CV2024
ViMoE: An Empirical Study of Designing Vision Mixture-of-Experts
Xumeng Han, Longhui Wei, Zhiyang Dou +6
Mixture-of-Experts (MoE) models embody the divide-and-conquer concept and are a promising approach for increasing model capacity, demonstrating excellent scalability across multipl…