:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Brahma, Debarshi, Biswas, Soma
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2506.03926
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts
by: Brahma, Debarshi, et al.
Published: (2025)

Vision-aware Multimodal Prompt Tuning for Uploadable Multi-source Few-shot Domain Adaptation
by: Liu, Kuanghong, et al.
Published: (2025)

Segmentation Assisted Incremental Test Time Adaptation in an Open World
by: Sreenivas, Manogna, et al.
Published: (2025)

Efficient Open Set Single Image Test Time Adaptation of Vision Language Models
by: Sreenivas, Manogna, et al.
Published: (2024)

E2MPL:An Enduring and Efficient Meta Prompt Learning Framework for Few-shot Unsupervised Domain Adaptation
by: Yang, Wanqi, et al.
Published: (2024)

Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings
by: Xue, Yihao, et al.
Published: (2023)

EV-CLIP: Efficient Visual Prompt Adaptation for CLIP in Few-shot Action Recognition under Visual Challenges
by: Jon, Hyo Jin, et al.
Published: (2026)

Parameter-efficient Prompt Tuning and Hierarchical Textual Guidance for Few-shot Whole Slide Image Classification
by: Bogahawatte, Jayanie, et al.
Published: (2026)

MSCPT: Few-shot Whole Slide Image Classification with Multi-scale and Context-focused Prompt Tuning
by: Han, Minghao, et al.
Published: (2024)

Few-shot Adaptation of Medical Vision-Language Models
by: Shakeri, Fereshteh, et al.
Published: (2024)

Enhancing Test Time Adaptation with Few-shot Guidance
by: Luo, Siqi, et al.
Published: (2024)

Decoupling Clinical and Class-Agnostic Features for Reliable Few-Shot Adaptation under Shift
by: Rahman, Umaima, et al.
Published: (2025)

AggSS: An Aggregated Self-Supervised Approach for Class-Incremental Learning
by: Kalla, Jayateja, et al.
Published: (2024)

Vision and Language Reference Prompt into SAM for Few-shot Segmentation
by: Sakurai, Kosuke, et al.
Published: (2025)

Retrieval-Enhanced Visual Prompt Learning for Few-shot Classification
by: Rong, Jintao, et al.
Published: (2023)

Step-wise Distribution Alignment Guided Style Prompt Tuning for Source-free Cross-domain Few-shot Learning
by: Xu, Huali, et al.
Published: (2024)

Few-shot Metric Domain Adaptation: Practical Learning Strategies for an Automated Plant Disease Diagnosis
by: Kudo, Shoma, et al.
Published: (2024)

Few-shot Adaptation of Multi-modal Foundation Models: A Survey
by: Liu, Fan, et al.
Published: (2024)

Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud Segmentation
by: Liu, Jie, et al.
Published: (2024)

CoDA: Instructive Chain-of-Domain Adaptation with Severity-Aware Visual Prompt Tuning
by: Gong, Ziyang, et al.
Published: (2024)

Prompt-and-Transfer: Dynamic Class-aware Enhancement for Few-shot Segmentation
by: Bi, Hanbo, et al.
Published: (2024)

Continual Few-shot Adaptation for Synthetic Fingerprint Detection
by: Benjamin, Joseph Geo, et al.
Published: (2026)

CoVLM: Leveraging Consensus from Vision-Language Models for Semi-supervised Multi-modal Fake News Detection
by: Devank, et al.
Published: (2024)

Unified Language-driven Zero-shot Domain Adaptation
by: Yang, Senqiao, et al.
Published: (2024)

DomainGallery: Few-shot Domain-driven Image Generation by Attribute-centric Finetuning
by: Duan, Yuxuan, et al.
Published: (2024)

ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift
by: Kashiani, Hossein, et al.
Published: (2024)

Revisiting Pool-based Prompt Learning for Few-shot Class-incremental Learning
by: Jiang, Yongwei, et al.
Published: (2025)

TAVP: Task-Adaptive Visual Prompt for Cross-domain Few-shot Segmentation
by: Yang, Jiaqi, et al.
Published: (2024)

Visual Prompting for Generalized Few-shot Segmentation: A Multi-scale Approach
by: Hossain, Mir Rayat Imtiaz, et al.
Published: (2024)

OpenKD: Opening Prompt Diversity for Zero- and Few-shot Keypoint Detection
by: Lu, Changsheng, et al.
Published: (2024)

Few-Shot Adaptation of Grounding DINO for Agricultural Domain
by: Singh, Rajhans, et al.
Published: (2025)

Low-Data Supervised Adaptation Outperforms Prompting for Cloud Segmentation Under Domain Shift
by: Kethavath, Harshith, et al.
Published: (2026)

Few-shot Writer Adaptation via Multimodal In-Context Learning
by: Simon, Tom, et al.
Published: (2026)

Domain Adaptation of Attention Heads for Zero-shot Anomaly Detection
by: Jeong, Kiyoon, et al.
Published: (2025)

TACLE: Task and Class-aware Exemplar-free Semi-supervised Class Incremental Learning
by: Kalla, Jayateja, et al.
Published: (2024)

AttriStory: Fine-grained Attribute Realization for Visual Storytelling with Diffusion Models
by: Sreenivas, Manogna, et al.
Published: (2026)

Dual-Adapter: Training-free Dual Adaptation for Few-shot Out-of-Distribution Detection
by: Chen, Xinyi, et al.
Published: (2024)

One2Avatar: Generative Implicit Head Avatar For Few-shot User Adaptation
by: Yu, Zhixuan, et al.
Published: (2024)

Task-Adapter: Task-specific Adaptation of Image Models for Few-shot Action Recognition
by: Cao, Congqi, et al.
Published: (2024)

Masked Language Prompting for Generative Data Augmentation in Few-shot Fashion Style Recognition
by: Hirakawa, Yuki, et al.
Published: (2025)