Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model
Fuente:
arXiv
Saved in:
| Main Authors: | Zhong, Jincheng, Zhang, Xiangcheng, Wang, Jianmin, Long, Mingsheng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting
by: Zhong, Jincheng, et al.
Published: (2024)
by: Zhong, Jincheng, et al.
Published: (2024)
Diffusion Models without Classifier-free Guidance
by: Tang, Zhicong, et al.
Published: (2025)
by: Tang, Zhicong, et al.
Published: (2025)
Slight Corruption in Pre-training Data Makes Better Diffusion Models
by: Chen, Hao, et al.
Published: (2024)
by: Chen, Hao, et al.
Published: (2024)
Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation
by: Um, Soobin, et al.
Published: (2025)
by: Um, Soobin, et al.
Published: (2025)
Dataset Ownership Verification in Contrastive Pre-trained Models
by: Xie, Yuechen, et al.
Published: (2025)
by: Xie, Yuechen, et al.
Published: (2025)
ReGuidance: A Simple Diffusion Wrapper for Boosting Sample Quality on Hard Inverse Problems
by: Karan, Aayush, et al.
Published: (2025)
by: Karan, Aayush, et al.
Published: (2025)
Learning Diffusion Models with Flexible Representation Guidance
by: Wang, Chenyu, et al.
Published: (2025)
by: Wang, Chenyu, et al.
Published: (2025)
Variational Control for Guidance in Diffusion Models
by: Pandey, Kushagra, et al.
Published: (2025)
by: Pandey, Kushagra, et al.
Published: (2025)
Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification
by: Chitnis, Soham Rohit, et al.
Published: (2023)
by: Chitnis, Soham Rohit, et al.
Published: (2023)
REG: Rectified Gradient Guidance for Conditional Diffusion Models
by: Gao, Zhengqi, et al.
Published: (2025)
by: Gao, Zhengqi, et al.
Published: (2025)
Practical Continual Forgetting for Pre-trained Vision Models
by: Zhao, Hongbo, et al.
Published: (2025)
by: Zhao, Hongbo, et al.
Published: (2025)
Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
by: Guo, Xingzhuo, et al.
Published: (2025)
by: Guo, Xingzhuo, et al.
Published: (2025)
Solving 3D Inverse Problems using Pre-trained 2D Diffusion Models
by: Chung, Hyungjin, et al.
Published: (2022)
by: Chung, Hyungjin, et al.
Published: (2022)
A Comparative Study of Custom CNNs, Pre-trained Models, and Transfer Learning Across Multiple Visual Datasets
by: Akhand, Annoor Sharara
Published: (2026)
by: Akhand, Annoor Sharara
Published: (2026)
Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models
by: Wu, Xiaoyu, et al.
Published: (2024)
by: Wu, Xiaoyu, et al.
Published: (2024)
Point-PEFT: Parameter-Efficient Fine-Tuning for 3D Pre-trained Models
by: Tang, Yiwen, et al.
Published: (2023)
by: Tang, Yiwen, et al.
Published: (2023)
NIL: No-data Imitation Learning by Leveraging Pre-trained Video Diffusion Models
by: Albaba, Mert, et al.
Published: (2025)
by: Albaba, Mert, et al.
Published: (2025)
Pre-training with Random Orthogonal Projection Image Modeling
by: Haghighat, Maryam, et al.
Published: (2023)
by: Haghighat, Maryam, et al.
Published: (2023)
Don't Play Favorites: Minority Guidance for Diffusion Models
by: Um, Soobin, et al.
Published: (2023)
by: Um, Soobin, et al.
Published: (2023)
Multi-modal Vision Pre-training for Medical Image Analysis
by: Rui, Shaohao, et al.
Published: (2024)
by: Rui, Shaohao, et al.
Published: (2024)
CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models
by: Chung, Hyungjin, et al.
Published: (2024)
by: Chung, Hyungjin, et al.
Published: (2024)
Feedback-based Modal Mutual Search for Attacking Vision-Language Pre-training Models
by: Ding, Renhua, et al.
Published: (2024)
by: Ding, Renhua, et al.
Published: (2024)
Transferability-Guided Cross-Domain Cross-Task Transfer Learning
by: Tan, Yang, et al.
Published: (2022)
by: Tan, Yang, et al.
Published: (2022)
A Noise is Worth Diffusion Guidance
by: Ahn, Donghoon, et al.
Published: (2024)
by: Ahn, Donghoon, et al.
Published: (2024)
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
by: Lai, Zhengfeng, et al.
Published: (2024)
by: Lai, Zhengfeng, et al.
Published: (2024)
SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-training
by: Zhang, Gengwei, et al.
Published: (2024)
by: Zhang, Gengwei, et al.
Published: (2024)
Gradient-based Fine-Tuning through Pre-trained Model Regularization
by: Liu, Xuanbo, et al.
Published: (2025)
by: Liu, Xuanbo, et al.
Published: (2025)
Where and How to Perturb: On the Design of Perturbation Guidance in Diffusion and Flow Models
by: Ahn, Donghoon, et al.
Published: (2025)
by: Ahn, Donghoon, et al.
Published: (2025)
Integrating Frequency Guidance into Multi-source Domain Generalization for Bearing Fault Diagnosis
by: Tu, Xiaotong, et al.
Published: (2025)
by: Tu, Xiaotong, et al.
Published: (2025)
When Test-Time Guidance Is Enough: Fast Image and Video Editing with Diffusion Guidance
by: Ghorbel, Ahmed, et al.
Published: (2026)
by: Ghorbel, Ahmed, et al.
Published: (2026)
Vehicle-centric Perception via Multimodal Structured Pre-training
by: Wu, Wentao, et al.
Published: (2025)
by: Wu, Wentao, et al.
Published: (2025)
Addressing Negative Transfer in Diffusion Models
by: Go, Hyojun, et al.
Published: (2023)
by: Go, Hyojun, et al.
Published: (2023)
Freeze the backbones: A Parameter-Efficient Contrastive Approach to Robust Medical Vision-Language Pre-training
by: Qin, Jiuming, et al.
Published: (2024)
by: Qin, Jiuming, et al.
Published: (2024)
Self-supervised Pre-training of Text Recognizers
by: Kišš, Martin, et al.
Published: (2024)
by: Kišš, Martin, et al.
Published: (2024)
Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control
by: Gupta, Gunshi, et al.
Published: (2024)
by: Gupta, Gunshi, et al.
Published: (2024)
Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-training Objective
by: Verma, Sahil, et al.
Published: (2023)
by: Verma, Sahil, et al.
Published: (2023)
Region-Aware Reconstruction Strategy for Pre-training fMRI Foundation Model
by: Doodipala, Ruthwik Reddy, et al.
Published: (2025)
by: Doodipala, Ruthwik Reddy, et al.
Published: (2025)
Closed-Form Linear-Probe Dataset Distillation for Pre-trained Vision Models
by: Peng, Bincheng, et al.
Published: (2026)
by: Peng, Bincheng, et al.
Published: (2026)
DASH: Dual-Branch Score Distillation for Guidance-Calibrated Compact Diffusion Models
by: Shafi, Abdullah Al, et al.
Published: (2026)
by: Shafi, Abdullah Al, et al.
Published: (2026)
Smoothed Energy Guidance: Guiding Diffusion Models with Reduced Energy Curvature of Attention
by: Hong, Susung
Published: (2024)
by: Hong, Susung
Published: (2024)
Similar Items
-
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting
by: Zhong, Jincheng, et al.
Published: (2024) -
Diffusion Models without Classifier-free Guidance
by: Tang, Zhicong, et al.
Published: (2025) -
Slight Corruption in Pre-training Data Makes Better Diffusion Models
by: Chen, Hao, et al.
Published: (2024) -
Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation
by: Um, Soobin, et al.
Published: (2025) -
Dataset Ownership Verification in Contrastive Pre-trained Models
by: Xie, Yuechen, et al.
Published: (2025)