conftrace_

out-of-distribution detection

617 papers

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Also known as

OODD OOD DETECTION

Co-occurring keywords

uncertainty quantification (1393) distribution shift (722) uncertainty estimation (648) anomaly detection (747) neural network (6616) ood detection (45) generative model (2892) representation learning (6206) domain generalization (1522) contrastive learning (4032)

Papers

Energy-based Epistemic Uncertainty for Graph Neural Networks NIPS 2024
Epistemic Uncertainty Quantification For Pre-Trained Neural Networks CVPR 2024
DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning NIPS 2024
RCL: Reliable Continual Learning for Unified Failure Detection CVPR 2024
Learning Structured Representations with Hyperbolic Embeddings NIPS 2024
MAGE: Machine-generated Text Detection in the Wild ACL 2024
EGonc : Energy-based Open-Set Node Classification with substitute Unknowns NIPS 2024
Universal Novelty Detection Through Adaptive Contrastive Learning CVPR 2024
Textual Training for the Hassle-Free Removal of Unwanted Visual Data: Case Studies on OOD and Hateful Image Detection NIPS 2024
Hyper-opinion Evidential Deep Learning for Out-of-Distribution Detection NIPS 2024
Out-of-Distribution Detection through Soft Clustering with Non-Negative Kernel Regression EMNLP 2024
Discriminability-Driven Channel Selection for Out-of-Distribution Detection CVPR 2024
Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks AISTATS 2024
CORES: Convolutional Response-based Score for Out-of-distribution Detection CVPR 2024
ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection CVPR 2024
Taming False Positives in Out-of-Distribution Detection with Human Feedback AISTATS 2024
The Best of Both Worlds: On the Dilemma of Out-of-distribution Detection NIPS 2024
Test-Time Linear Out-of-Distribution Detection CVPR 2024
Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts NIPS 2024
What If the Input is Expanded in OOD Detection? NIPS 2024
Rethinking Safe Semi-supervised Learning: Transferring the Open-set Problem to A Close-set One ICCV 2023
Triple-Hybrid Energy-based Model Makes Better Calibrated Natural Language Understanding Models EACL 2023
Flexible Visual Recognition by Evidential Modeling of Confusion and Ignorance ICCV 2023
Why Out-of-Distribution detection experiments are not reliable - subtle experimental details muddle the OOD detector rankings UAI 2023
Logit-based ensemble distribution distillation for robust autoregressive sequence uncertainties UAI 2023