3 papers
cs.CV2026
Attention Transfer Is Not Universally Effective for Vision Transformers
Huaiyuan Qin, Muli Yang, Gabriel James Goenawan +4
A recent work shows that Attention Transfer, which transfers only the attention patterns from a pre-trained teacher Vision Transformer (ViT) to a randomly initialized standard stud…
cs.CV2026
Beyond Loss Values: Robust Dynamic Pruning via Loss Trajectory Alignment
Huaiyuan Qin, Muli Yang, Gabriel James Goenawan +5
Existing dynamic data pruning methods often fail under noisy-label settings, as they typically rely on per-sample loss as the ranking criterion. This could mistakenly lead to prese…
cs.CV2026
Your AI-Generated Image Detector Can Secretly Achieve SOTA Accuracy, If Calibrated
Muli Yang, Gabriel James Goenawan, Henan Wang +7
Despite being trained on balanced datasets, existing AI-generated image detectors often exhibit systematic bias at test time, frequently misclassifying fake images as real. We hypo…