8 citations · 13 across the 12 of their papers we have counts for
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cs.CV2025
UR-Bench: A Benchmark for Multi-Hop Reasoning over Ultra-High-Resolution Images
Siqi Li, Xinyu Cai, Jianbiao Mei +7
Recent multimodal large language models (MLLMs) show strong capabilities in visual-language reasoning, yet their performance on ultra-high-resolution imagery remains largely unexpl…
cs.CV2025★ 4 cited
InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
Weiyun Wang, Zhangwei Gao, Lixin Gu +72
We introduce InternVL 3.5, a new family of open-source multimodal models that significantly advances versatility, reasoning capability, and inference efficiency along the InternVL…
cs.CV2025
InternSpatial: A Comprehensive Dataset for Spatial Reasoning in Vision-Language Models
Nianchen Deng, Lixin Gu, Shenglong Ye +17
Recent benchmarks and datasets have been proposed to improve spatial reasoning in vision-language models (VLMs), yet existing open resources remain limited in scale, visual diversi…