5 papers
PerturbBridge: Direct Phenotypic Supervision for Cellular Perturbation Generation
Yucheng Yang, Xiaoxiao Sun, Huangqingbo Sun +3
Virtual cell models should capture phenotypes induced by specific perturbations. However, image-based models are typically trained and evaluated to match real-image distributions,…
ScreenHaystack: Finding Blind Zones in GUI Grounding
Chenyue Li, Xiaoxiao Sun, Yubo Deng +3
We introduce ScreenHaystack, a dynamic needle-in-a-haystack benchmark for evaluating spatial reliability in GUI grounding. Instead of testing each target at a fixed position, Scree…
Solve the Missing First Step: Can VLMs Standardize Raw Heterogeneous Medical Data?
Xin Chen, Dongliang Xu, Cunhao Zhu +5
As vision-language models (VLMs) are increasingly applied to medical AI, existing benchmarks mainly focus on evaluating their diagnostic ability over given medical images and texts…
Do VLMs Perceive or Recall? Probing Visual Perception vs. Memory with Classic Visual Illusions
Xiaoxiao Sun, Mingyang Li, Kun Yuan +7
Large Vision-Language Models (VLMs) often answer classic visual illusions "correctly" on original images, yet persist with the same responses when illusion factors are inverted, ev…
From Panel to Pixel: Zoom-In Vision-Language Pretraining from Biomedical Scientific Literature
Kun Yuan, Min Woo Sun, Zhen Chen +7
There is a growing interest in developing strong biomedical vision-language models. A popular approach to achieve robust representations is to use web-scale scientific data. Howeve…