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iFAN boosts segmentation accuracy by aligning query competition with mask quality, achieving significant performance gains without extra computational overhead.
Textual shortcuts in VLMs can significantly undermine reasoning accuracy, but a simple intervention can restore fresh visual computation.
Achieving superior instruction accuracy and edit fidelity, GMO-E$^2$DIT redefines how we approach multi-operation image editing in e-commerce.
