3 papers
cs.CV2026
How Do Medical MLLMs Fail? A Study on Visual Grounding in Medical Images
Guimeng Liu, Tianze Yu, Somayeh Ebrahimkhani +3
Generalist multimodal large language models (MLLMs) have achieved impressive performance across a wide range of vision-language tasks. However, their performance on medical tasks,…
cs.CV2026
A Survey on Generative Modeling with Limited Data, Few Shots, and Zero Shot
Milad Abdollahzadeh, Guimeng Liu, Touba Malekzadeh +3
Generative modeling in machine learning aims to synthesize new data samples that are statistically similar to those observed during training. While conventional generative models s…
cs.CV2025
AIR: Zero-shot Generative Model Adaptation with Iterative Refinement
Guimeng Liu, Milad Abdollahzadeh, Ngai-Man Cheung
Zero-shot generative model adaptation (ZSGM) aims to adapt a pre-trained generator to a target domain using only text guidance and without any samples from the target domain. Centr…