Cover Image

The Invisible Gorilla Effect in Out-of-distribution Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Anthony, Harry, Liang, Ziyun, Warr, Hermione, Kamnitsas, Konstantinos
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Semi-Supervised Learning for Deep Causal Generative Models
by: Ibrahim, Yasin, et al.
Published: (2024)

Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection
by: Anthony, Harry, et al.
Published: (2024)

Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components
by: Warr, Hermione, et al.
Published: (2024)

IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI
by: Liang, Ziyun, et al.
Published: (2024)

IterMask3D: Unsupervised Anomaly Detection and Segmentation with Test-Time Iterative Mask Refinement in 3D Brain MR
by: Liang, Ziyun, et al.
Published: (2025)

DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging
by: Wagner, Felix, et al.
Published: (2025)

You Point, I Learn: Online Adaptation of Interactive Segmentation Models for Handling Distribution Shifts in Medical Imaging
by: Xu, Wentian, et al.
Published: (2025)

Specialised or Generic? Tokenization Choices for Radiology Language Models
by: Warr, Hermione, et al.
Published: (2025)

On the Learnability of Out-of-distribution Detection
by: Fang, Zhen, et al.
Published: (2024)

Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection
by: Saha, Pramit, et al.
Published: (2024)

Class Relevance Learning For Out-of-distribution Detection
by: Xiong, Butian, et al.
Published: (2023)

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning
by: Saha, Pramit, et al.
Published: (2024)

Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models
by: Peng, Bo, et al.
Published: (2026)

RankFeat&RankWeight: Rank-1 Feature/Weight Removal for Out-of-distribution Detection
by: Song, Yue, et al.
Published: (2023)

Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection
by: Zhao, Qinyu, et al.
Published: (2024)

Activation Subspaces for Out-of-Distribution Detection
by: Zöngür, Barış, et al.
Published: (2025)

Out-of-Distribution Detection with Relative Angles
by: Demirel, Berker, et al.
Published: (2024)

Gradient-Regularized Out-of-Distribution Detection
by: Sharifi, Sina, et al.
Published: (2024)

Out-Of-Distribution Detection with Diversification (Provably)
by: Yao, Haiyun, et al.
Published: (2024)

Distribution Shifts at Scale: Out-of-distribution Detection in Earth Observation
by: Ekim, Burak, et al.
Published: (2024)

Out-of-distribution detection using normalizing flows on the data manifold
by: Razavi, Seyedeh Fatemeh, et al.
Published: (2023)

F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics
by: Saha, Pramit, et al.
Published: (2024)

Vendi Novelty Scores for Out-of-Distribution Detection
by: Pasarkar, Amey P., et al.
Published: (2026)

Learning with Mixture of Prototypes for Out-of-Distribution Detection
by: Lu, Haodong, et al.
Published: (2024)

Out-of-distribution evaluations of channel agnostic masked autoencoders in fluorescence microscopy
by: Hurry, Christian John, et al.
Published: (2025)

Generalized Categories Discovery for Long-tailed Recognition
by: Li, Ziyun, et al.
Published: (2023)

Shaping Parameter Contribution Patterns for Out-of-Distribution Detection
by: Xu, Haonan, et al.
Published: (2026)

Network Inversion for Uncertainty-Aware Out-of-Distribution Detection
by: Suhail, Pirzada, et al.
Published: (2025)

Toward a Realistic Benchmark for Out-of-Distribution Detection
by: Recalcati, Pietro, et al.
Published: (2024)

Energy-based Hopfield Boosting for Out-of-Distribution Detection
by: Hofmann, Claus, et al.
Published: (2024)

Iterative Deployment Exposure for Unsupervised Out-of-Distribution Detection
by: Doorenbos, Lars, et al.
Published: (2024)

Are We Ready for Out-of-Distribution Detection in Digital Pathology?
by: Oh, Ji-Hun, et al.
Published: (2024)

Hypercone Assisted Contour Generation for Out-of-Distribution Detection
by: Vapsi, Annita, et al.
Published: (2025)

NODI: Out-Of-Distribution Detection with Noise from Diffusion
by: Zhou, Jingqiu, et al.
Published: (2024)

Evaluation of Out-of-Distribution Detection Performance on Autonomous Driving Datasets
by: Henriksson, Jens, et al.
Published: (2024)

OODD: Test-time Out-of-Distribution Detection with Dynamic Dictionary
by: Yang, Yifeng, et al.
Published: (2025)

Detecting Out-of-Distribution Objects through Class-Conditioned Inpainting
by: Nguyen, Quang-Huy, et al.
Published: (2024)

NERO: Explainable Out-of-Distribution Detection with Neuron-level Relevance
by: Chhetri, Anju, et al.
Published: (2025)

Out-of-Distribution Detection & Applications With Ablated Learned Temperature Energy
by: LeVine, Will, et al.
Published: (2024)

Revisiting Likelihood-Based Out-of-Distribution Detection by Modeling Representations
by: Ding, Yifan, et al.
Published: (2025)