SOTAVerified

Out of Distribution (OOD) Detection

Out of Distribution (OOD) Detection is the task of detecting instances that do not belong to the distribution the classifier has been trained on. OOD data is often referred to as "unseen" data, as the model has not encountered it during training.

OOD detection is typically performed by training a model to distinguish between in-distribution (ID) data, which the model has seen during training, and OOD data, which it has not seen. This can be done using a variety of techniques, such as training a separate OOD detector, or modifying the model's architecture or loss function to make it more sensitive to OOD data.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 226–250 of 629 papers

TitleStatusHype
Exploiting Mixed Unlabeled Data for Detecting Samples of Seen and Unseen Out-of-Distribution Classes—0
Exploiting Diffusion Prior for Out-of-Distribution Detection—0
Evaluation of Out-of-Distribution Detection Performance of Self-Supervised Learning in a Controllable Environment—0
General-Purpose Multi-Modal OOD Detection Framework—0
GLIP-OOD: Zero-Shot Graph OOD Detection with Graph Foundation Model—0
A Deep Generative Distance-Based Classifier for Out-of-Domain Detection with Mahalanobis Space—0
Joint Distribution across Representation Space for Out-of-Distribution Detection—0
Joint Learning of Domain Classification and Out-of-Domain Detection with Dynamic Class Weighting for Satisficing False Acceptance Rates—0
Detecting Compositionally Out-of-Distribution Examples in Semantic Parsing—0
Label Smoothed Embedding Hypothesis for Out-of-Distribution Detection—0
Graph Synthetic Out-of-Distribution Exposure with Large Language Models—0
GRODIN: Improved Large-Scale Out-of-Domain detection via Back-propagation—0
GROOD: Gradient-Aware Out-of-Distribution Detection—0
Evaluating the Practical Utility of Confidence-score based Techniques for Unsupervised Open-world Classification—0
Estimating Soft Labels for Out-of-Domain Intent Detection—0
EPA: Neural Collapse Inspired Robust Out-of-Distribution Detector—0
Interpretable Out-Of-Distribution Detection Using Pattern Identification—0
Entropic Issues in Likelihood-Based OOD Detection—0
Enhancing Trustworthiness in ML-Based Network Intrusion Detection with Uncertainty Quantification—0
Histogram- and Diffusion-Based Medical Out-of-Distribution Detection—0
Holistic Sentence Embeddings for Better Out-of-Distribution Detection—0
HOOD: Real-Time Human Presence and Out-of-Distribution Detection Using FMCW Radar—0
How Does Fine-Tuning Impact Out-of-Distribution Detection for Vision-Language Models?—0
A Variational Information Theoretic Approach to Out-of-Distribution Detection—0
Enhancing the Generalization for Intent Classification and Out-of-Domain Detection in SLU—0
Show:102550
← PrevPage 10 of 26Next →

No leaderboard results yet.