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Concept-Guided Fine-Tuning: Steering ViTs away from Spurious Correlations to Improve Robustness
Vision Transformers (ViTs) often degrade under distribution shifts because they rely on spurious correlations, such as background cues, rather than semantically meaningful features. Existing regularization methods, typically relying on simple foreground-background masks, which fail to capture the fi
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