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arXiv AI By Youngeun Seol, Jimin Shin, Heeseo Yoon, Uiwon Hwang

Domain Recentering and Confidence-Weighted Prior Calibration for Vision-Language Models

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The paper introduces Domain Recentering with Confidence Calibration (DRC), a training‑free technique that adapts CLIP to unlabeled target images by fitting a Gaussian mixture and subtracting a posterior‑weighted average of component means from each embedding. It further corrects residual class bias using a log‑prior adjustment based on confidence‑weighted predictions. DRC outperforms other methods, raising average accuracy on cross‑domain datasets by 4.13 and 5.07 points over zero‑shot CLIP for ViT‑B/16 and ResNet‑50, and maintains gains under ImageNet distribution shifts.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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