PLSP (Pre-hoc Liminal Space Profiling): OOD Prediction over Detection -- An Anticipatory Approach for Machine Learning Model Reliability

arXiv:2609.12225 · cs.LG, cs.CV · Submitted 2026-09-10 · Read on arXiv

cs.LG, cs.CV

Submitted: 2026-09-10

Updated: 2026-10-15

Comments: 10 pages, 3 figures, 5 tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• AUC — 1× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Pre-hoc Liminal Space Profiling — 1× in this paper
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• Generalized Out-of-Distribution Detection: A Survey
• Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions
• Exploring the Limits of Out-of-Distribution Detection
• Contrastive Training for Improved Out-of-Distribution Detection
• Heterogeneous Risk Minimization
• Domain Generalization: A Survey
• Out-of-Distribution Generalization Analysis via Influence Function
• OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization
• Improve Unsupervised Domain Adaptation with Mixup Training
• On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions
• Do CIFAR-10 Classifiers Generalize to CIFAR-10?

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