This work introduces CAST (Closed-form Analytic Semantic Transfer), a training-free, image-free framework for extending a pre-trained classifier to previously unseen classes through weight injection and derives a finite-sample error decomposition that identifies the semantic extrapolation residual.
W. Heyden, Habib Ullah, M. Siddiqui et al.· 0 citations
A few-shot regression framework that combines Vision Transformer feature embeddings, clustering-based task construction, and gradient-based meta-learning is proposed, and it is shown that task construction in embedding space is a primary driver of performance.
Sheikh Hasan Elahi, R. Dewage, Habib Ullah et al.· 0 citations
Diversify, Anchor, and Filter (DAF), a stabilization framework that augments entropy-based adaptation with a marginal diversity loss that resists collapse, a cross-modal anchor consistency loss that constrains feature drift relative to a frozen source model, and feature salience filtering that skips low-value backward...
Chandler Timm C. Doloriel, Yunbei Zhang, Sarthak Kumar Maharana et al.· 0 citations
Sensitivity-Guided Erasing Adaptation (SEGA) is introduced, a method for strict online continual TTA (CTTA) on corruption-style streams that yields consistent robustness and stability gains over strong CTTA baselines while reducing backward passes through sensitivity-based gating.
Chandler Timm C. Doloriel, Yun-Bei Zhang, M. Siddiqui et al.· 0 citations
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