mlsanityData to 14 Oct 2026

Exploiting Diffusion Prior for Out-of-Distribution Detection

arXiv 2406.11105 ↗First posted 16 Jun 2024cs.CV cs.AIcited by 7

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Out-of-distribution (OOD) detection is crucial for deploying robust machine learning models, especially in areas where security is critical. However, traditional OOD detection methods often fail to capture complex data distributions from large scale date. In this paper, we present a novel approach for OOD detection that leverages the generative ability of diffusion models and the powerful feature extraction capabilities of CLIP. By using these features as conditional inputs to a diffusion model, we can reconstruct the images after encoding them with CLIP. The difference between the original and reconstructed images is used as a signal for OOD identification. The practicality and scalability of our method is increased by the fact that it does not require class-specific labeled ID data, as is the case with many other methods. Extensive experiments on several benchmark datasets demonstrates the robustness and effectiveness of our method, which have significantly improved the detection accuracy.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 63 of its 101 references that are in the map. First posted on arXiv 16 Jun 2024.

Builds on

63 of 101 references.

References · 63

  1. 2017Attention Is All You Needcited by 60,361
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  4. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  5. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  6. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
  7. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,152
  8. 2016Simple and Scalable Predictive Uncertainty Estimation using Deep Ensemblescited by 3,926
  9. 2016A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networkscited by 2,385
  10. 2013Describing Textures in the Wildcited by 2,125
  11. 2018Glow: Generative Flow with Invertible 1x1 Convolutionscited by 1,545
  12. 2018A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attackscited by 1,485
38 more
  1. 2022Conditional Prompt Learning for Vision-Language Modelscited by 1,433
  2. 2017Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networkscited by 1,328
  3. 2022Reproducible scaling laws for contrastive language-image learningcited by 1,173
  4. 2021Generalized Out-of-Distribution Detection: A Surveycited by 802
  5. 2022Out-of-Distribution Detection with Deep Nearest Neighborscited by 600
  6. 2019Scaling Out-of-Distribution Detection for Real-World Settingscited by 465
  7. 2022ViM: Out-Of-Distribution with Virtual-logit Matchingcited by 405
  8. 2018Learning Confidence for Out-of-Distribution Detection in Neural Networkscited by 245
  9. 2022Delving into Out-of-Distribution Detection with Vision-Language Representationscited by 216
  10. 2023CLIPN for Zero-Shot OOD Detection: Teaching CLIP to Say Nocited by 130
  11. 2023Thread of Thought Unraveling Chaotic Contextscited by 72
  12. 2023PLGSLAM: Progressive Neural Scene Represenation with Local to Global Bundle Adjustmentcited by 63
  13. 2023VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understandingcited by 62
  14. 2023Deception Detection from Linguistic and Physiological Data Streams Using Bimodal Convolutional Neural Networkscited by 56
  15. 2024Exploring Diverse Methods in Visual Question Answeringcited by 45
  16. 2018Contextual Hourglass Network for Semantic Segmentation of High Resolution Aerial Imagerycited by 43
  17. 2023MmAP : Multi-modal Alignment Prompt for Cross-domain Multi-task Learningcited by 41
  18. 2022Towards Robust Ranker for Text Retrievalcited by 37
  19. 2023GL-MCM: Global and Local Maximum Concept Matching for Zero-Shot Out-of-Distribution Detectioncited by 36
  20. 2024Regional Style and Color Transfercited by 30
  21. 2022Fine-Grained Distillation for Long Document Retrievalcited by 29
  22. 2023Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Modelscited by 27
  23. 2019Novelty Detection Via Blurringcited by 24
  24. 2021Multimodal Semi-Supervised Learning for 3D Objectscited by 24
  25. 2024Large Language Model (LLM) AI text generation detection based on transformer deep learning algorithmcited by 23
  26. 2024RAG-RLRC-LaySum at BioLaySumm: Integrating Retrieval-Augmented Generation and Readability Control for Layman Summarization of Biomedical Textscited by 23
  27. 2019Confidence Trigger Detection: Accelerating Real-time Tracking-by-detection Systemscited by 21
  28. 2023Multimodal Event Transformer for Image-guided Story Ending Generationcited by 21
  29. 2023Improving Cross-modal Alignment for Text-Guided Image Inpaintingcited by 21
  30. 2023Style-Aware Contrastive Learning for Multi-Style Image Captioningcited by 21
  31. 2024A Comparative Study on Enhancing Prediction in Social Network Advertisement through Data Augmentationcited by 21
  32. 2024Research on Splicing Image Detection Algorithms Based on Natural Image Statistical Characteristicscited by 21
  33. 2024Rumor Detection with a novel graph neural network approachcited by 15
  34. 2024Incremental Joint Learning of Depth, Pose and Implicit Scene Representation on Monocular Camera in Large-scale Scenescited by 15
  35. 2024Adaptive speed planning for Unmanned Vehicle Based on Deep Reinforcement Learningcited by 15
  36. 2022Class-Level Confidence Based 3D Semi-Supervised Learningcited by 14
  37. 2024Efficiency optimization of large-scale language models based on deep learning in natural language processing taskscited by 14
  38. 2023Prediction of COVID-19 Patients' Emergency Room Revisit using Multi-Source Transfer Learningcited by 11

50 most cited of 63 All 63 (JSON)

Built on by

Cited by year

Citing papers per year: 2024: 3; 2025: 4.

7 papers.

  1. 2024Optimizing Automated Picking Systems in Warehouse Robots Using Machine Learningcited by 20
  2. 2024Enhanced Recommendation Combining Collaborative Filtering and Large Language Modelscited by 10
  3. 2025Research on the Design of a Short Video Recommendation System Based on Multimodal Information and Differential Privacycited by 9
  4. 2025User Behavior Analysis in Privacy Protection with Large Language Models: A Study on Privacy Preferences with Limited Datacited by 8
  5. 2025Outlier Synthesis via Hamiltonian Monte Carlo for Out-of-Distribution Detectioncited by 4
  6. 2024Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generationcited by 2
  7. 2025Generating Multimodal Images with GAN: Integrating Text, Image, and Stylecited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024NODI: Out-Of-Distribution Detection with Noise from Diffusion
  2. 2025Beyond Binary Out-of-Distribution Detection: Characterizing Distributional Shifts with Multi-Statistic Diffusion Trajectories
  3. 2024Enhancing OOD Detection Using Latent Diffusion
  4. 2025Probability Density from Latent Diffusion Models for Out-of-Distribution Detection
  5. 2025Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey
  6. 2024Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution Detection
  7. 2024Out-of-Distribution Detection with a Single Unconditional Diffusion Model
  8. 2026Geometry over Density: Few-Shot Cross-Domain OOD Detection