Threshold transfer for CoRegOVCD’s final mask inference
Determine whether and under what conditions the fixed decision thresholds used in CoRegOVCD’s final mask inference can transfer across datasets, classes, and imaging conditions without dataset-specific tuning, and establish principled strategies for threshold selection if transferability is limited.
References
Prompt robustness, threshold transfer, and efficient multi-concept inference remain open, but the central conclusion is clear: posterior differencing, once properly regularized, provides a stronger foundation for training-free OVCD.
The per-image oracle consumes ground truth and is only a diagnostic; selecting a stable threshold across new image domains remains open.
The relative contributions of threshold-selection variability, cohort composition, and changes in the score--correctness relation remain unresolved.
Refitted on $\tau2$-bench, the cheapest delegation that passed lost \resabs{primaries/C7/jev/delta} points, so we could not show it transfers.