Replacing softmax with a one-vs-each Polya-Gamma augmented objective plus a logit-matching penalty improves unseen-class and cross-dataset accuracy across CoOp, CoCoOp, MaPLe, and APEX.
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Bayesian Principles Improve Prompt Learning In Vision-Language Models
Replacing softmax with a one-vs-each Polya-Gamma augmented objective plus a logit-matching penalty improves unseen-class and cross-dataset accuracy across CoOp, CoCoOp, MaPLe, and APEX.