2025 "out-of-distribution detection" Papers
43 papers found
$\Delta \mathrm{Energy}$: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization
Lin Zhu, Yifeng Yang, Xinbing Wang et al.
Advancing Out-of-Distribution Detection via Local Neuroplasticity
Alessandro Canevaro, Julian Schmidt, Sajad Marvi et al.
An Empirical Analysis of Uncertainty in Large Language Model Evaluations
Qiujie Xie, Qingqiu Li, Zhuohao Yu et al.
An Information-theoretical Framework for Understanding Out-of-distribution Detection with Pretrained Vision-Language Models
Bo Peng, Jie Lu, Guangquan Zhang et al.
Any-Resolution AI-Generated Image Detection by Spectral Learning
Dimitrios Karageorgiou, Symeon Papadopoulos, Ioannis Kompatsiaris et al.
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar et al.
Detecting Out-of-Distribution Through the Lens of Neural Collapse
Litian Liu, Yao Qin
DisCoPatch: Taming Adversarially-driven Batch Statistics for Improved Out-of-Distribution Detection
Francisco Caetano, Christiaan Viviers, Luis Zavala-Mondragón et al.
DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging
Felix Wagner, Pramit Saha, Harry Anthony et al.
DPU: Dynamic Prototype Updating for Multimodal Out-of-Distribution Detection
Li Li, Huixian Gong, Hao Dong et al.
Efficient Active Imitation Learning with Random Network Distillation
Emilien Biré, Anthony Kobanda, Ludovic Denoyer et al.
Equipping Vision Foundation Model with Mixture of Experts for Out-of-Distribution Detection
Shizhen Zhao, Jiahui Liu, Xin Wen et al.
ETA: Energy-based Test-time Adaptation for Depth Completion
Younjoon Chung, Hyoungseob Park, Patrick Rim et al.
Extremely Simple Multimodal Outlier Synthesis for Out-of-Distribution Detection and Segmentation
Moru Liu, Hao Dong, Jessica Kelly et al.
From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation
Nikita Kotelevskii, Vladimir Kondratyev, Martin Takáč et al.
H2ST: Hierarchical Two-Sample Tests for Continual Out-of-Distribution Detection
Yuhang Liu, Wenjie Zhao, Yunhui Guo
Harnessing Feature Resonance under Arbitrary Target Alignment for Out-of-Distribution Node Detection
Shenzhi Yang, Junbo Zhao, Sharon Li et al.
Joint Out-of-Distribution Filtering and Data Discovery Active Learning
Sebastian Schmidt, Leonard Schenk, Leo Schwinn et al.
MetaOOD: Automatic Selection of OOD Detection Models
Yuehan Qin, Yichi Zhang, Yi Nian et al.
Mysteries of the Deep: Role of Intermediate Representations in Out of Distribution Detection
Ignacio Meza De la Jara, Cristian Rodriguez-Opazo, Damien Teney et al.
Noisy Test-Time Adaptation in Vision-Language Models
Chentao Cao, Zhun Zhong, (Andrew) Zhanke Zhou et al.
On Large Language Model Continual Unlearning
Chongyang Gao, Lixu Wang, Kaize Ding et al.
OOD-Barrier: Build a Middle-Barrier for Open-Set Single-Image Test Time Adaptation via Vision Language Models
Boyang Peng, Sanqing Qu, Tianpei Zou et al.
OOD Detection with Relative Angles
Berker Demirel, Marco Fumero, Francesco Locatello
OODD: Test-time Out-of-Distribution Detection with Dynamic Dictionary
Yifeng Yang, Lin Zhu, Zewen Sun et al.
Outlier Synthesis via Hamiltonian Monte Carlo for Out-of-Distribution Detection
Hengzhuang Li, Teng Zhang
Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function
Linlin Yu, Bowen Yang, Tianhao Wang et al.
Prior2Former - Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation
Sebastian Schmidt, Julius Koerner, Dominik Fuchsgruber et al.
Provably Safeguarding a Classifier from OOD and Adversarial Samples
Nicolas Atienza, Johanne Cohen, Christophe Labreuche et al.
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection
Yingwen Wu, Ruiji Yu, Xinwen Cheng et al.
Refining Norms: A Post-hoc Framework for OOD Detection in Graph Neural Networks
Jiawei Gu, Ziyue Qiao, Zechao Li
Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generation
Jihyo Kim, Seulbi Lee, Sangheum Hwang
Rethinking Out-of-Distribution Detection and Generalization with Collective Behavior Dynamics
Zhenbin Wang, Lei Zhang, Wei Huang et al.
Revisiting Logit Distributions for Reliable Out-of-Distribution Detection
Jiachen Liang, RuiBing Hou, Minyang Hu et al.
Spreading Out-of-Distribution Detection on Graphs
Daeho Um, Jongin Lim, Sunoh Kim et al.
The Illusion of Progress? A Critical Look at Test-Time Adaptation for Vision-Language Models
Lijun Sheng, Jian Liang, Ran He et al.
Tight Asymptotics of Extreme Order Statistics
Matias Romero, Frederik Mallmann-Trenn, Jose Correa
Towards Generalizable Detector for Generated Image
Qianshu Cai, Chao Wu, Yonggang Zhang et al.
Towards Understanding and Quantifying Uncertainty for Text-to-Image Generation
Gianni Franchi, Nacim Belkhir, Dat NGUYEN et al.
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka et al.
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark
Yili Wang, Yixin Liu, Xu Shen et al.
Vicinal Label Supervision for Reliable Aleatoric and Epistemic Uncertainty Estimation
Linye Li, Yufei Chen, Xiaodong Yue
X-Mahalanobis: Transformer Feature Mixing for Reliable OOD Detection
Tong Wei, Bolin Wang, Jiang-Xin Shi et al.