Decoupling Template Bias in CLIP: Harnessing Empty Prompts for Enhanced Few-Shot Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Zhenyu, Chen, Guangyao, Zou, Yixiong, Huang, Zhimeng, Li, Yuhua |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Mind the Discriminability Trap in Source-Free Cross-domain Few-shot Learning
by: Zhang, Zhenyu, et al.
Published: (2026)
by: Zhang, Zhenyu, et al.
Published: (2026)
Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
by: Tong, Jintao, et al.
Published: (2025)
by: Tong, Jintao, et al.
Published: (2025)
MICM: Rethinking Unsupervised Pretraining for Enhanced Few-shot Learning
by: Zhang, Zhenyu, et al.
Published: (2024)
by: Zhang, Zhenyu, et al.
Published: (2024)
Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
by: Tong, Jintao, et al.
Published: (2025)
by: Tong, Jintao, et al.
Published: (2025)
Compositional Few-Shot Class-Incremental Learning
by: Zou, Yixiong, et al.
Published: (2024)
by: Zou, Yixiong, et al.
Published: (2024)
Interpretable Cross-Domain Few-Shot Learning with Rectified Target-Domain Local Alignment
by: Zhao, Yaze, et al.
Published: (2026)
by: Zhao, Yaze, et al.
Published: (2026)
Learning Unknowns from Unknowns: Diversified Negative Prototypes Generator for Few-Shot Open-Set Recognition
by: Zhang, Zhenyu, et al.
Published: (2024)
by: Zhang, Zhenyu, et al.
Published: (2024)
Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation
by: Tong, Jintao, et al.
Published: (2024)
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)
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)
by: Zou, Yixiong, et al.
Published: (2024)
Delve into Base-Novel Confusion: Redundancy Exploration for Few-Shot Class-Incremental Learning
by: Zhou, Haichen, et al.
Published: (2024)
by: Zhou, Haichen, et al.
Published: (2024)
Topology-Aware CLIP Few-Shot Learning
by: Huang, Dazhi
Published: (2025)
by: Huang, Dazhi
Published: (2025)
Reviving In-domain Fine-tuning Methods for Source-Free Cross-domain Few-shot Learning
by: Zhao, Yaze, et al.
Published: (2026)
by: Zhao, Yaze, et al.
Published: (2026)
Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning
by: Yi, Shuai, et al.
Published: (2026)
by: Yi, Shuai, et al.
Published: (2026)
Few-Shot Remote Sensing Image Scene Classification with CLIP and Prompt Learning
by: Dimitrovski, Ivica, et al.
Published: (2025)
by: Dimitrovski, Ivica, et al.
Published: (2025)
Transductive Zero-Shot and Few-Shot CLIP
by: Martin, Ségolène, et al.
Published: (2024)
by: Martin, Ségolène, et al.
Published: (2024)
Reclaiming Lost Text Layers for Source-Free Cross-Domain Few-Shot Learning
by: Zhang, Zhenyu, et al.
Published: (2026)
by: Zhang, Zhenyu, et al.
Published: (2026)
Random Registers for Cross-Domain Few-Shot Learning
by: Yi, Shuai, et al.
Published: (2025)
by: Yi, Shuai, et al.
Published: (2025)
Revisiting Pool-based Prompt Learning for Few-shot Class-incremental Learning
by: Jiang, Yongwei, et al.
Published: (2025)
by: Jiang, Yongwei, et al.
Published: (2025)
GiPL: Generative augmented iterative Pseudo-Labeling for Cross-Domain Few-Shot Object Detection
by: Liu, Jiacong, et al.
Published: (2026)
by: Liu, Jiacong, et al.
Published: (2026)
Addressing Exacerbated Attention Sink for Source-Free Cross-Domain Few-Shot Learning
by: Yi, Shuai, et al.
Published: (2026)
by: Yi, Shuai, et al.
Published: (2026)
Reconstruction Target Matters in Masked Image Modeling for Cross-Domain Few-Shot Learning
by: Ma, Ran, et al.
Published: (2024)
by: Ma, Ran, et al.
Published: (2024)
Reinforcement Learning-Based Prompt Template Stealing for Text-to-Image Models
by: Zou, Xiaotian
Published: (2025)
by: Zou, Xiaotian
Published: (2025)
Few-Shot Pattern Detection via Template Matching and Regression
by: Jo, Eunchan, et al.
Published: (2025)
by: Jo, Eunchan, et al.
Published: (2025)
Remedying Target-Domain Astigmatism for Cross-Domain Few-Shot Object Detection
by: Jiang, Yongwei, et al.
Published: (2026)
by: Jiang, Yongwei, et al.
Published: (2026)
Few-Shot Object Detection via Spatial-Channel State Space Model
by: Xin, Zhimeng, et al.
Published: (2025)
by: Xin, Zhimeng, et al.
Published: (2025)
Few-Shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt
by: Liu, Chenxi, et al.
Published: (2024)
by: Liu, Chenxi, et al.
Published: (2024)
HiDe: Rethinking The Zoom-IN method in High Resolution MLLMs via Hierarchical Decoupling
by: Liu, Xianjie, et al.
Published: (2025)
by: Liu, Xianjie, et al.
Published: (2025)
Decoupling Augmentation Bias in Prompt Learning for Vision-Language Models
by: Kim, Gahyeon, et al.
Published: (2025)
by: Kim, Gahyeon, et al.
Published: (2025)
Semantic Relation-Enhanced CLIP Adapter for Domain Adaptive Zero-Shot Learning
by: Yu, Jiaao, et al.
Published: (2025)
by: Yu, Jiaao, et al.
Published: (2025)
SAPL: Semantic-Agnostic Prompt Learning in CLIP for Weakly Supervised Image Manipulation Localization
by: Wang, Xinghao, et al.
Published: (2026)
by: Wang, Xinghao, et al.
Published: (2026)
One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning
by: Zhou, Chunpeng, et al.
Published: (2025)
by: Zhou, Chunpeng, et al.
Published: (2025)
Exploring Cross-Domain Few-Shot Classification via Frequency-Aware Prompting
by: Zhang, Tiange, et al.
Published: (2024)
by: Zhang, Tiange, et al.
Published: (2024)
ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection
by: Bai, Yichen, et al.
Published: (2023)
by: Bai, Yichen, et al.
Published: (2023)
Foundation Visual Encoders Are Secretly Few-Shot Anomaly Detectors
by: Zhai, Guangyao, et al.
Published: (2025)
by: Zhai, Guangyao, et al.
Published: (2025)
Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning
by: Yi, Shuai, et al.
Published: (2025)
by: Yi, Shuai, et al.
Published: (2025)
Decouple before Align: Visual Disentanglement Enhances Prompt Tuning
by: Zhang, Fei, et al.
Published: (2025)
by: Zhang, Fei, et al.
Published: (2025)
PGP-SAM: Prototype-Guided Prompt Learning for Efficient Few-Shot Medical Image Segmentation
by: Yan, Zhonghao, et al.
Published: (2025)
by: Yan, Zhonghao, et al.
Published: (2025)
RAP: Retrieve, Adapt, and Prompt-Fit for Training-Free Few-Shot Medical Image Segmentation
by: Mao, Zhihao, et al.
Published: (2026)
by: Mao, Zhihao, et al.
Published: (2026)
Rethinking the Sample Relations for Few-Shot Classification
by: Yin, Guowei, et al.
Published: (2025)
by: Yin, Guowei, et al.
Published: (2025)
Similar Items
-
Mind the Discriminability Trap in Source-Free Cross-domain Few-shot Learning
by: Zhang, Zhenyu, et al.
Published: (2026) -
Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
by: Tong, Jintao, et al.
Published: (2025) -
MICM: Rethinking Unsupervised Pretraining for Enhanced Few-shot Learning
by: Zhang, Zhenyu, et al.
Published: (2024) -
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)