Cover Image

Mind the Gap Between Prototypes and Images in Cross-domain Finetuning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tian, Hongduan, Liu, Feng, Zhou, Zhanke, Liu, Tongliang, Zhang, Chengqi, Han, Bo
Format:	Preprint
Published:	2024
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

MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence
by: Tian, Hongduan, et al.
Published: (2024)

Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
by: Zhang, Jiacheng, et al.
Published: (2024)

Mind the Gap: Learning Modality-Agnostic Representations with a Cross-Modality UNet
by: Niu, Xin, et al.
Published: (2026)

Negative Label Guided OOD Detection with Pretrained Vision-Language Models
by: Jiang, Xue, et al.
Published: (2024)

BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning
by: Zhang, Jingfeng, et al.
Published: (2023)

Rethinking Model Selection in VLM Through the Lens of Gromov-Wasserstein Distance
by: Li, Muyang, et al.
Published: (2026)

Mind the Gap: Preserving and Compensating for the Modality Gap in CLIP-Based Continual Learning
by: Huang, Linlan, et al.
Published: (2025)

Controlling Text-to-Image Diffusion by Orthogonal Finetuning
by: Qiu, Zeju, et al.
Published: (2023)

Mind the Domain Gap: Measuring the Domain Gap Between Real-World and Synthetic Point Clouds for Automated Driving Development
by: Duc, Nguyen, et al.
Published: (2025)

Few-Shot Adversarial Prompt Learning on Vision-Language Models
by: Zhou, Yiwei, et al.
Published: (2024)

Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype
by: Qin, Anyong, et al.
Published: (2025)

Closing the Alignment-Maturity Gap in Federated Prototype Learning
by: Casado-Diez, Mario, et al.
Published: (2026)

Mind the Gap: Confidence Discrepancy Can Guide Federated Semi-Supervised Learning Across Pseudo-Mismatch
by: Liu, Yijie, et al.
Published: (2025)

Few-Shot Recognition via Stage-Wise Retrieval-Augmented Finetuning
by: Liu, Tian, et al.
Published: (2024)

Toward Modality Gap: Vision Prototype Learning for Weakly-supervised Semantic Segmentation with CLIP
by: Xu, Zhongxing, et al.
Published: (2024)

Approximate Nullspace Augmented Finetuning for Robust Vision Transformers
by: Liu, Haoyang, et al.
Published: (2024)

Mind the Gap: Continuous Magnification Sampling for Pathology Foundation Models
by: Möllers, Alexander, et al.
Published: (2026)

TRACER: Persistent Regularization for Robust Multimodal Finetuning
by: Asadollahzadeh, Hesam, et al.
Published: (2026)

Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels
by: Tian, Yuxin, et al.
Published: (2024)

Exploiting Fine-Grained Prototype Distribution for Boosting Unsupervised Class Incremental Learning
by: Liu, Jiaming, et al.
Published: (2024)

Task Matrices: Linear Maps for Cross-Model Finetuning Transfer
by: Brien, Darrin O', et al.
Published: (2025)

Omnimodal Dataset Distillation via High-order Proxy Alignment
by: Gao, Yuxuan, et al.
Published: (2026)

Mitigating the Modality Gap: Few-Shot Out-of-Distribution Detection with Multi-modal Prototypes and Image Bias Estimation
by: Wang, Yimu, et al.
Published: (2025)

ProCNS: Progressive Prototype Calibration and Noise Suppression for Weakly-Supervised Medical Image Segmentation
by: Liu, Y., et al.
Published: (2024)

Mind the (Language) Gap: Towards Probing Numerical and Cross-Lingual Limits of LVLMs
by: Gautam, Somraj, et al.
Published: (2025)

Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains
by: Wang, Lei, et al.
Published: (2024)

Geometry-aware Prototype Learning for Cross-domain Few-shot Medical Image Segmentation
by: Song, Feifan, et al.
Published: (2026)

Toward Robust Non-Transferable Learning: A Survey and Benchmark
by: Hong, Ziming, et al.
Published: (2025)

Semi-MedRef: Semi-Supervised Medical Referring Image Segmentation with Cross-Modal Alignment
by: Li, Yuchen, et al.
Published: (2026)

AdLift: Lifting Adversarial Perturbations to Safeguard 3D Gaussian Splatting Assets Against Instruction-Driven Editing
by: Hong, Ziming, et al.
Published: (2025)

When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need
by: Hong, Ziming, et al.
Published: (2025)

InfoNCE: Identifying the Gap Between Theory and Practice
by: Rusak, Evgenia, et al.
Published: (2024)

Beyond ImageNet: Understanding Cross-Dataset Robustness of Lightweight Vision Models
by: Zhang, Weidong, et al.
Published: (2025)

DINO-Detect: A Simple yet Effective Framework for Blur-Robust AI-Generated Image Detection
by: Shen, Jialiang, et al.
Published: (2025)

Tied Prototype Model for Few-Shot Medical Image Segmentation
by: Kim, Hyeongji, et al.
Published: (2025)

Finetuning CLIP to Reason about Pairwise Differences
by: Sam, Dylan, et al.
Published: (2024)

Revisiting Mixout: An Overlooked Path to Robust Finetuning
by: Aminbeidokhti, Masih, et al.
Published: (2025)

FOR: Finetuning for Object Level Open Vocabulary Image Retrieval
by: Levi, Hila, et al.
Published: (2024)

SubFlow: Sub-mode Conditioned Flow Matching for Diverse One-Step Generation
by: Lin, Yexiong, et al.
Published: (2026)

Orthogonal Finetuning Made Scalable
by: Qiu, Zeju, et al.
Published: (2025)