Copertina

Prompt Optimization Meets Subspace Representation Learning for Few-shot Out-of-Distribution Detection

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Sayem, Faizul Rakib, Ibrahim, Shahana
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Pseudo-label Induced Subspace Representation Learning for Robust Out-of-Distribution Detection
di: Azad, Tarhib Al, et al.
Pubblicazione: (2025)

ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection
di: Bai, Yichen, et al.
Pubblicazione: (2023)

Learning Multi-Manifold Embedding for Out-Of-Distribution Detection
di: Li, Jeng-Lin, et al.
Pubblicazione: (2024)

Compressing Model with Few Class-Imbalance Samples: An Out-of-Distribution Expedition
di: Wu, Tian-Shuang, et al.
Pubblicazione: (2025)

Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imaging
di: Fan, Keqiang, et al.
Pubblicazione: (2024)

Buffer-free Class-Incremental Learning with Out-of-Distribution Detection
di: Gupta, Srishti, et al.
Pubblicazione: (2025)

Learning Non-Linear Invariants for Unsupervised Out-of-Distribution Detection
di: Doorenbos, Lars, et al.
Pubblicazione: (2024)

Logit Scaling for Out-of-Distribution Detection
di: Djurisic, Andrija, et al.
Pubblicazione: (2024)

Lightweight Model for Poultry Disease Detection from Fecal Images Using Multi-Color Space Feature Optimization and Machine Learning
di: Islam, A. K. M. Shoriful, et al.
Pubblicazione: (2025)

Generalized Out-of-Distribution Detection: A Survey
di: Yang, Jingkang, et al.
Pubblicazione: (2021)

Concept Matching with Agent for Out-of-Distribution Detection
di: Lee, Yuxiao, et al.
Pubblicazione: (2024)

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection
di: Adethya, Gokul, et al.
Pubblicazione: (2025)

Frustratingly Easy Feature Reconstruction for Out-of-Distribution Detection
di: Wang, Yingsheng, et al.
Pubblicazione: (2025)

Advancing Out-of-Distribution Detection via Local Neuroplasticity
di: Canevaro, Alessandro, et al.
Pubblicazione: (2025)

Non-Linear Outlier Synthesis for Out-of-Distribution Detection
di: Doorenbos, Lars, et al.
Pubblicazione: (2024)

Diffusion for Out-of-Distribution Detection on Road Scenes and Beyond
di: Galesso, Silvio, et al.
Pubblicazione: (2024)

Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection
di: Guille-Escuret, Charles, et al.
Pubblicazione: (2023)

Anomaly Multi-classification in Industrial Scenarios: Transferring Few-shot Learning to a New Task
di: Liu, Jie, et al.
Pubblicazione: (2024)

MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities
di: Dong, Hao, et al.
Pubblicazione: (2024)

Energy Correction Model in the Feature Space for Out-of-Distribution Detection
di: Lafon, Marc, et al.
Pubblicazione: (2024)

Detecting Out-Of-Distribution Earth Observation Images with Diffusion Models
di: Bellier, Georges Le, et al.
Pubblicazione: (2024)

Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble
di: Xu, Chenhui, et al.
Pubblicazione: (2024)

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

Identity Curvature Laplace Approximation for Improved Out-of-Distribution Detection
di: Zhdanov, Maksim, et al.
Pubblicazione: (2023)

Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation
di: Mistretta, Marco, et al.
Pubblicazione: (2024)

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

Adaptive Prompt Tuning: Vision Guided Prompt Tuning with Cross-Attention for Fine-Grained Few-Shot Learning
di: Brouwer, Eric, et al.
Pubblicazione: (2024)

Few-Shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt
di: Liu, Chenxi, et al.
Pubblicazione: (2024)

TriAug: Out-of-Distribution Detection for Imbalanced Breast Lesion in Ultrasound
di: Ye, Yinyu, et al.
Pubblicazione: (2024)

Can Your Generative Model Detect Out-of-Distribution Covariate Shift?
di: Viviers, Christiaan, et al.
Pubblicazione: (2024)

Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection
di: Yu, Geng, et al.
Pubblicazione: (2024)

Improving Out-of-Distribution Detection by Combining Existing Post-hoc Methods
di: Novello, Paul, et al.
Pubblicazione: (2024)

Enhancing Out-of-Distribution Detection with Multitesting-based Layer-wise Feature Fusion
di: Li, Jiawei, et al.
Pubblicazione: (2024)

A Systematic Comparison of Training Objectives for Out-of-Distribution Detection in Image Classification
di: Genç, Furkan, et al.
Pubblicazione: (2026)

Meta-Prompting for Automating Zero-shot Visual Recognition with LLMs
di: Mirza, M. Jehanzeb, et al.
Pubblicazione: (2024)

Subspace Kernel Learning on Tensor Sequences
di: Wang, Lei, et al.
Pubblicazione: (2026)

Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey
di: Miyai, Atsuyuki, et al.
Pubblicazione: (2024)

Unsupervised Contrastive Learning Using Out-Of-Distribution Data for Long-Tailed Dataset
di: Hoang, Cuong Manh, et al.
Pubblicazione: (2025)

LSPT: Long-term Spatial Prompt Tuning for Visual Representation Learning
di: Mo, Shentong, et al.
Pubblicazione: (2024)

Extremely Simple Multimodal Outlier Synthesis for Out-of-Distribution Detection and Segmentation
di: Liu, Moru, et al.
Pubblicazione: (2025)