Cover Image

Addressing Exacerbated Attention Sink for Source-Free Cross-Domain Few-Shot Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yi, Shuai, Zou, Yixiong, Li, Yuhua, Li, Ruixuan
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning
by: Yi, Shuai, et al.
Published: (2026)

Random Registers for Cross-Domain Few-Shot Learning
by: Yi, Shuai, et al.
Published: (2025)

Remedying Target-Domain Astigmatism for Cross-Domain Few-Shot Object Detection
by: Jiang, Yongwei, et al.
Published: (2026)

Reconstruction Target Matters in Masked Image Modeling for Cross-Domain Few-Shot Learning
by: Ma, Ran, et al.
Published: (2024)

Interpretable Cross-Domain Few-Shot Learning with Rectified Target-Domain Local Alignment
by: Zhao, Yaze, et al.
Published: (2026)

Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning
by: Yi, Shuai, et al.
Published: (2025)

Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation
by: Tong, Jintao, et al.
Published: (2024)

The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation
by: Liu, Yuhan, et al.
Published: (2025)

Flatten Long-Range Loss Landscapes for Cross-Domain Few-Shot Learning
by: Zou, Yixiong, et al.
Published: (2024)

Mind the Discriminability Trap in Source-Free Cross-domain Few-shot Learning
by: Zhang, Zhenyu, et al.
Published: (2026)

Reviving In-domain Fine-tuning Methods for Source-Free Cross-domain Few-shot Learning
by: Zhao, Yaze, et al.
Published: (2026)

Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
by: Tong, Jintao, et al.
Published: (2025)

Compositional Few-Shot Class-Incremental Learning
by: Zou, Yixiong, et al.
Published: (2024)

Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
by: Tong, Jintao, et al.
Published: (2025)

Learning Unknowns from Unknowns: Diversified Negative Prototypes Generator for Few-Shot Open-Set Recognition
by: Zhang, Zhenyu, et al.
Published: (2024)

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

Delve into Base-Novel Confusion: Redundancy Exploration for Few-Shot Class-Incremental Learning
by: Zhou, Haichen, et al.
Published: (2024)

MICM: Rethinking Unsupervised Pretraining for Enhanced Few-shot Learning
by: Zhang, Zhenyu, et al.
Published: (2024)

Decoupling Template Bias in CLIP: Harnessing Empty Prompts for Enhanced Few-Shot Learning
by: Zhang, Zhenyu, et al.
Published: (2025)

Enhancing Information Maximization with Distance-Aware Contrastive Learning for Source-Free Cross-Domain Few-Shot Learning
by: Xu, Huali, et al.
Published: (2024)

Free Lunch to Meet the Gap: Intermediate Domain Reconstruction for Cross-Domain Few-Shot Learning
by: Zhang, Tong, et al.
Published: (2025)

Cross-Domain Few-Shot Learning via Multi-View Collaborative Optimization with Vision-Language Models
by: Chen, Dexia, et al.
Published: (2025)

GiPL: Generative augmented iterative Pseudo-Labeling for Cross-Domain Few-Shot Object Detection
by: Liu, Jiacong, et al.
Published: (2026)

Reclaiming Lost Text Layers for Source-Free Cross-Domain Few-Shot Learning
by: Zhang, Zhenyu, et al.
Published: (2026)

Asymmetric Co-Training for Source-Free Few-Shot Domain Adaptation
by: Li, Gengxu, et al.
Published: (2025)

Adapting In-Domain Few-Shot Segmentation to New Domains without Source Domain Retraining
by: Fan, Qi, et al.
Published: (2025)

Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey
by: Xu, Huali, et al.
Published: (2023)

CMP: A Composable Meta Prompt for SAM-Based Cross-Domain Few-Shot Segmentation
by: Chen, Shuai, et al.
Published: (2025)

MindShot: A Few-Shot Brain Decoding Framework via Transferring Cross-Subject Prior and Distilling Frequency Domain Knowledge
by: Jiang, Shuai, et al.
Published: (2024)

Few-Shot Object Detection via Spatial-Channel State Space Model
by: Xin, Zhimeng, et al.
Published: (2025)

DMSD-CDFSAR: Distillation from Mixed-Source Domain for Cross-Domain Few-shot Action Recognition
by: Guo, Fei, et al.
Published: (2024)

Textual and Visual Guided Task Adaptation for Source-Free Cross-Domain Few-Shot Segmentation
by: Liu, Jianming, et al.
Published: (2025)

Domain-Rectifying Adapter for Cross-Domain Few-Shot Segmentation
by: Su, Jiapeng, et al.
Published: (2024)

CASP: Few-Shot Class-Incremental Learning with CLS Token Attention Steering Prompts
by: Huang, Shuai, et al.
Published: (2026)

Multimodal Cross-Domain Few-Shot Learning for Egocentric Action Recognition
by: Hatano, Masashi, et al.
Published: (2024)

Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning
by: Zhou, Fei, et al.
Published: (2024)

FlowCut: Rethinking Redundancy via Information Flow for Efficient Vision-Language Models
by: Tong, Jintao, et al.
Published: (2025)

A Cross-Domain Few-Shot Learning Method Based on Domain Knowledge Mapping
by: Chen, Jiajun, et al.
Published: (2025)

Contrastive Graph Modeling for Cross-Domain Few-Shot Medical Image Segmentation
by: Bo, Yuntian, et al.
Published: (2025)

Preserve and Sculpt: Manifold-Aligned Fine-tuning of Vision-Language Models for Few-Shot Learning
by: Chen, Dexia, et al.
Published: (2025)