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IEEE/ICACT20250021 Slide.19        [Big Slide]	Oral Presentation
	Right now, GenImage has some issues—like corrupted images, biased features, too much redundancy, and not enough diversity in the model. But we think these are fixable, and improving them will make the model more reliable. Next, ViT-L/14 used in our work isn¡¯t necessarily the best option since there are newer CLIP models that perform better. So, we¡¯re looking into stronger backbones to see if we can boost accuracy and generalization. Finally, if we can get the model to focus on where anomalies actually happen, it could generalize even better. The idea is to add some reasoning ability so the model isn¡¯t just spotting patterns but actually understanding what makes something abnormal.

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