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This paper introduces a protocol for fair comparison of diffusion-based OOD detectors and proposes Canonical Feature Snapshots (CFS), which leverage sparse internal activations for efficient detection.
CPCANet is a domain generalization framework that uses Common Principal Component Analysis to discover structured domain-invariant subspaces, achieving state-of-the-art performance in zero-shot transfer.
This paper proposes CAP-TTA, a test-time adaptation framework that uses preconditioned LoRA updates triggered by bias-risk scores to mitigate toxicity and bias in large language models during narrative generation, achieving faster optimization and better fluency than standard baselines.