SMI replaces MIA-based unlearned model auditing with training-free statistical estimation of non-member mixture proportions in feature space, yielding reliable forgetting rates and bootstrap reliability ranges.
Structured Defect Grounding models text-to-image failures as structured tuples for diagnosis and alignment, outperforming proprietary vision-language models and improving generation via importance-weighted rewards.
A frozen vision-language-action model improves test-time reliability by retrieving past successful actions to guide flow-matching generation without parameter updates.
COVD enables continual open-vocabulary detection via novel concept injection, and NoIn-Det freezes visual encoders to align text representations with new concepts without extra parameters, outperforming existing continual methods on Novel-114.