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cs.AI2026
Contextualized Evaluation of Vision Language Models through Dynamic, Multi-turn Interactions
Yijiang Li, Huiqi Zou, Bingyang Wang +1
Multi-modal Large Language Models (MLLMs) have made substantial advances on benchmarks, yet their real-world effectiveness remains uncertain. This gap stems from the fundamental mi…
cs.AI2026
SPACENUM: Revisiting Spatial Numerical Understanding in VLMs
Jianshu Zhang, Yijiang Li, Huifeixin Chen +4
Vision-Language Models (VLMs) are increasingly deployed in embodied environments, where they need produce numerical outputs such as action magnitudes and spatial coordinates. Altho…
cs.AI2026
Vision Language Models Cannot Reason About Physical Transformation
Dezhi Luo, Yijiang Li, Maijunxian Wang +7
Understanding physical transformations is fundamental for reasoning in dynamic environments. While Vision Language Models (VLMs) show promise in embodied applications, whether they…