OOD Detection

OOD: Out-of-Distribution

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10 papers in the last four weeks, up 11% on the four weeks before. 0.1% of all new papers.

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Theoretical Grounding of Out-Of-Distribution Detection With Reinforcement Learning Optimizer
Jun 16, 2026Salimeh Sekeh, Xin ZhangOOD Generalization OOD Detection
San Diego State University
MM++: Post-Hoc Scale-Invariant Multilayer OOD Detection via Top-K Gated Feature Fusion
Jun 15, 2026Rahim Hossain, Md Tawheedul Islam Bhuian, Md Farhan Shadiq +1Diffusion-Based OOD Detection OOD Detection
School of Computing State University of New York at Binghamton
Semantic Flip: Synthetic OOD Generation for Robust Refusal in Embodied Question Answering and Spatial Localization
Jun 15, 2026Dongbin Na, Chanwoo Kim, Giyun Choi +1Synthetic Data Generation Embodied QA
RGA Inc.
When Confidence Lacks Concepts: Interpretable OOD Detection via Representation Perturbations
Jun 15, 2026Anju Chhetri, Pratik Shrestha, Ramesh Rana +3Medical Image Anomaly Detection Neural Network Interpretability
NepAl Applied Mathematics and Informatics Institute for research, Nepal · Kathmandu University, Nepal · NHS Grampian, UK +3
Sensitivity Shaping for Latent Modeling
Jun 12, 2026Hongzhan Yu, Chenghao Li, Ruipeng Zhang +2Robotic Control Latent Dynamics Modeling
University of California San Diego
Out-of-Distribution (OOD) Detectors for Open-Set RF Fingerprinting
Jun 10, 2026Sudeepta Mondal, Ganesh SundaramoorthiOpen-Set Recognition OOD Detection
RTX Technology Research Center (RTRC).
TaskFusion: Continual Anomaly Detection for Heterogeneous Tabular Data
Jun 10, 2026Dayananda Herurkar, Federico Raue, Joachim Folz +2Tabular Anomaly Detection Continual Learning
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany · RPTU Kaiserslautern-Landau, Germany · Hochschule Bonn-Rhein-Sieg (H-BRS), Germany
Mahalanobis-Guided Latent OOD Detection for Hybrid ES-DRL Control in Time-Varying Systems
Jun 9, 2026Shaifalee Saxena, Alexander ScheinkerRL Control Feedback Control
Los Alamos National Laboratory, Los Alamos, New Mexico, USA · University of New Mexico, New Mexico, USA
SafeECGMatch: Calibration-Aware Joint Frequency and Time Space Semi-Supervised Learning for Open-Set ECG Classification
Jun 6, 2026Hongkyu Koh, Ikbeom JangProbability Calibration Open-Set Recognition
Hankuk University of Foreign Studies · Yongin, Republic of Korea
GP-Adapter: Gaussian Process CLIP-Adapter for Few-Shot Out-of-Distribution Detection
Jun 5, 2026Taisei Saito, Koretaka Ogata, Takafumi HiroiVLM Adaptation Few-Shot Image Classification
Ricoh Company, Ltd. Ebina, Japan
Dual Feature Decoupling for Fine-Grained OOD Detection
Jun 4, 2026Xiaokun Li, Yaping Huang, Qingji GuanRepresentation Disentanglement OOD Detection
School of Computer Science and Technology, Beijing Jiaotong University, No. 3 Shangyuan Village, Haidian District, Beijing, China
Need We Teach Foundation Models What is a Generative Image? Gradient-Free Generative Artifact Detection via Analytic Spectral Adaptation
Jun 3, 2026Qiaoyu Chen, Bing ZhangVision Foundation Model Adaptation AI-Generated Image Detection
Harbin University of Commerce
High-Precision APT Malware Attribution with Out-of-Scope Resilience
Jun 2, 2026Peter Williams, Adam Sobey, Erisa KarafiliSelective Prediction Malware Classification
University of Southampton, Southampton, UK · The Alan Turing Institute, London, UK
FlowGuard: Flow Matching for Identity-Independent Detection of Data-Free Model Stealing Attacks on Energy System Intrusion Detection Systems
Jun 2, 2026Maxime Schwarzer, Laurin Holz, Tobias Huerten +4Model Extraction Attacks Network Intrusion Detection
CortAIx Labs, Thales Deutschland / Karlsruhe Institute of Technology Germany · CortAIx Labs, Thales Deutschland Germany · Karlsruhe Institute of Technology Germany
A Closer Look at In-Distribution vs. Out-of-Distribution Accuracy for Open-Set Test-time Adaptation
Jun 1, 2026Zefeng Li, Evan ShelhamerTest-Time Adaptation Open-Set Recognition
University of British Columbia and Vector Institute
Local Diagnostics of Continuous Normalizing Flow for Out-of-Distribution Detection
May 30, 2026Xinwei Cao, Mengxuan Lu, Torbjørn Svendsen +1Speech Processing Distribution Shift Detection
Department of Electronic Systems Norwegian University of Science and Technology Trondheim, Norway · School of Future Technology South China University of Technology Guangzhou, China
KLIP: localized distribution shift detection via KL-divergence with diffusion priors in Inverse Problems
May 29, 2026Alireza Kheirandish, Jihoon Hong, Sara Fridovich-KeilDiffusion-Based OOD Detection Distribution Shift Detection
Georgia Institute of Technology
Learning Hyperspherical Time-Frequency Representations for Time-Series Out-of-Distribution Detection
May 29, 2026Willian T. Lunardi, Samridha Shrestha, Martin AndreoniHyperspherical Representation Learning Distribution Shift Detection
Technology Innovation Institute, Abu Dhabi, United Arab Emirates · Khalifa University, Abu Dhabi, United Arab Emirates
Immuno-VLM: Immunizing Large Vision-Language Models via Generative Semantic Antibodies for Open-World Trustworthiness
May 29, 2026Xiang Fang, Wanlong Fang, Wei JiVLM Robustness Large Vision-Language Models
School of Software Engineering, Huazhong University of Science and Technology · Nanyang Technological University, Singapore · Nanjing University
Active Continual Learning with Metaplastic Binary Bayesian Neural Networks
May 28, 2026Kellian Cottart, Théo Ballet, Djohan Bonnet +1Bayesian Neural Networks Binary Neural Networks
Université Paris-Saclay, CNRS, Centre de Nanosciences et de Nanotechnologies, Palaiseau, France · Forschungszentrum Jülich, Germany
Open World Autoencoding Drift Detection with Novel Class Recognition in Tabular Non-stationary Data Streams
May 28, 2026Joanna KomorniczakConcept Drift Autoencoders
Department of Systems and Computer Networks, Wrocław University of Science and Technology
Energy-Aware NECO for Single-Pass Pixel-wise Out-of-Distribution Detection in Semantic Segmentation
May 28, 2026Boyuan Zhang, Huanshan Huang, Yifei CaoImage Segmentation OOD Detection
Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France. · CIAD, UTBM, Universit´e Marie et Louis Pasteur, France. · U2IS, ENSTA, Institut Polytechnique de Paris, France.
Temporal Motif-aware Graph Test-time Adaptation for OOD Blockchain Anomaly Detection
May 28, 2026Runang He, Tongya Zheng, Huiling Peng +6Temporal GNNs Test-Time Adaptation
State Key Laboratory of Blockchain and Data Security, Zhejiang University · Zhejiang Provincial Engineering Research Center for Real-Time SmartTech in Urban Security Governance, Hangzhou City University · Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security
AOE: Exhaustive Out-of-Distribution Detection via Recalibrating Outlier Labels
May 27, 2026Fengqiang Wan, Qing-Yuan Jiang, Yang YangOOD Detection
School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Respecting Modality Gap in Post-hoc Out-of-distribution Detection with Pre-trained Vision-Language Models
May 26, 2026Yuanwei Hu, Bo Peng, Yadan Luo +3Vision-Language Models Test-Time Adaptation
University of Technology Sydney · The University of Queensland
Structure-Adaptive Conformal Inference for Large-Scale Out-of-Distribution Testing
May 26, 2026Rongyi Sun, Wenguang Sun, Zinan ZhaoFDR Control Conformal Prediction
Center for Data Science and School of Mathematical Sciences, Zhejiang University. · Center for Data Science and School of Management, Zhejiang University.
Can Predicted Dynamics Exist in the Physical World?
May 23, 2026Barak OrRobotic Control Model-Based Planning
STATE16 Founder and CEO, STATE16
Catching magnetic resonance imaging outliers in artificial intelligence-supported radiotherapy workflows: unsupervised detection and localization of image anomalies using deep learning
May 23, 2026Mustafa Kadhim, Viktor Rogowski, Emilia Persson +7Medical Image Anomaly Detection Anomaly Localization
Medical Radiation Physics, Lund University, Lund, Sweden. · Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Lund, Sweden. · Medical Radiation Physics, Department of Translational Medicine, Lund University, Malmö, Sweden +4
Testing the Test: Score-Direction Instability in Class-Split Anomaly Detection
May 23, 2026Alejandro Ascarate, Leo Lebrat, Rodrigo Santa Cruz +2OOD Detection Anomaly Detection
School of Electrical Engineering and Robotics, Faculty of Engineering, Queensland University of Technology, Brisbane, Queensland, Australia.
Generative OOD-regularized Model-based Policy Optimization
May 23, 2026Aysin Tumay, Jiahe Huang, Elise Jortberg +1Offline RL OOD Detection
University of California, San Diego · Abiomed

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Theoretical Grounding of Out-Of-Distribution Detection With Reinforcement Learning Optimizer

Salimeh Sekeh, Xin Zhang

San Diego State University

OOD Generalization OOD Detection

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Out-of-distribution (OOD) detection in dynamic open-world environments requires a model to continually adapt to evolving data distributions while generalizing to covariate-shifted inputs and rejecting semantic-shifted OOD examples. Most existing OOD detection methods optimize only the current-step objective and do not explicitly account for how post-deployment environment changes affect future OOD behavior. In this paper, we establish a theoretical grounding for dynamic OOD detection using a reinforcement learning (RL)-guided optimizer that explicitly favors updates that reduce the semantic OOD false positive rate over time. We develop a novel augmented optimizer that uses an RL-guided correction term on top of standard gradient descent (GD) and show its improvement over both future-domain generalization and semantic-OOD rejection. We analyze temporal error decomposition in terms of model-change and environment-change generalization errors and develop a new theoretical framework for comparing the generalization errors under both GD and RL-guided optimizers.

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