Match & Choose: Model Selection Framework for Fine-tuning Text-to-Image Diffusion Models
Fuente:
arXiv
Saved in:
| Main Authors: | Lewandowski, Basile, Birke, Robert, Chen, Lydia Y. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
TMPDiff: Temporal Mixed-Precision for Diffusion Models
by: Lewandowski, Basile, et al.
Published: (2026)
by: Lewandowski, Basile, et al.
Published: (2026)
Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation
by: Yuan, Huizhuo, et al.
Published: (2024)
by: Yuan, Huizhuo, et al.
Published: (2024)
CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching
by: Jiang, Dongzhi, et al.
Published: (2024)
by: Jiang, Dongzhi, et al.
Published: (2024)
MPQ-Diff: Mixed Precision Quantization for Diffusion Models
by: Maruzzelli, Rocco Manz, et al.
Published: (2024)
by: Maruzzelli, Rocco Manz, et al.
Published: (2024)
Efficient Model Editing with Task-Localized Sparse Fine-tuning
by: Iurada, Leonardo, et al.
Published: (2025)
by: Iurada, Leonardo, et al.
Published: (2025)
CRCE: Coreference-Retention Concept Erasure in Text-to-Image Diffusion Models
by: Xue, Yuyang, et al.
Published: (2025)
by: Xue, Yuyang, et al.
Published: (2025)
Reward Score Matching: Unifying Reward-based Fine-tuning for Flow and Diffusion Models
by: Lee, Jeongjae, et al.
Published: (2026)
by: Lee, Jeongjae, et al.
Published: (2026)
Towards the Resistance of Neural Network Watermarking to Fine-tuning
by: Tang, Ling, et al.
Published: (2025)
by: Tang, Ling, et al.
Published: (2025)
Efficient Pruning of Text-to-Image Models: Insights from Pruning Stable Diffusion
by: Ramesh, Samarth N, et al.
Published: (2024)
by: Ramesh, Samarth N, et al.
Published: (2024)
A Simple and Effective Reinforcement Learning Method for Text-to-Image Diffusion Fine-tuning
by: Gupta, Shashank, et al.
Published: (2025)
by: Gupta, Shashank, et al.
Published: (2025)
DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models
by: Chae, Daewon, et al.
Published: (2025)
by: Chae, Daewon, et al.
Published: (2025)
Flexible-length Text Infilling for Discrete Diffusion Models
by: Zhang, Andrew, et al.
Published: (2025)
by: Zhang, Andrew, et al.
Published: (2025)
LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention
by: Zhang, Renrui, et al.
Published: (2023)
by: Zhang, Renrui, et al.
Published: (2023)
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)
Alignment-Guided Score Matching for Text-to-Image Alignment in Diffusion Models
by: Lee, Jaa-Yeon, et al.
Published: (2026)
by: Lee, Jaa-Yeon, et al.
Published: (2026)
Stylus: Automatic Adapter Selection for Diffusion Models
by: Luo, Michael, et al.
Published: (2024)
by: Luo, Michael, et al.
Published: (2024)
Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model
by: Yang, Kai, et al.
Published: (2023)
by: Yang, Kai, et al.
Published: (2023)
DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
by: Shi, Zhengxiang, et al.
Published: (2023)
by: Shi, Zhengxiang, et al.
Published: (2023)
SurGen: Text-Guided Diffusion Model for Surgical Video Generation
by: Cho, Joseph, et al.
Published: (2024)
by: Cho, Joseph, et al.
Published: (2024)
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation
by: Cho, Jaemin, et al.
Published: (2023)
by: Cho, Jaemin, et al.
Published: (2023)
A Generalist Model for Diverse Text-Guided Medical Image Synthesis
by: Cho, Joseph, et al.
Published: (2024)
by: Cho, Joseph, et al.
Published: (2024)
Unaligning Everything: Or Aligning Any Text to Any Image in Multimodal Models
by: Salman, Shaeke, et al.
Published: (2024)
by: Salman, Shaeke, et al.
Published: (2024)
Draw Your Mind: Personalized Generation via Condition-Level Modeling in Text-to-Image Diffusion Models
by: Kim, Hyungjin, et al.
Published: (2025)
by: Kim, Hyungjin, et al.
Published: (2025)
A Comparative Study of Machine Unlearning Techniques for Image and Text Classification Models
by: Safa, Omar M., et al.
Published: (2024)
by: Safa, Omar M., et al.
Published: (2024)
Safety Alignment Backfires: Preventing the Re-emergence of Suppressed Concepts in Fine-tuned Text-to-Image Diffusion Models
by: Kim, Sanghyun, et al.
Published: (2024)
by: Kim, Sanghyun, et al.
Published: (2024)
Multi-Modal Language Models as Text-to-Image Model Evaluators
by: Chen, Jiahui, et al.
Published: (2025)
by: Chen, Jiahui, et al.
Published: (2025)
Fine-Grained Image-Text Alignment in Medical Imaging Enables Explainable Cyclic Image-Report Generation
by: Chen, Wenting, et al.
Published: (2023)
by: Chen, Wenting, et al.
Published: (2023)
ComCLIP: Training-Free Compositional Image and Text Matching
by: Jiang, Kenan, et al.
Published: (2022)
by: Jiang, Kenan, et al.
Published: (2022)
Erasing with Precision: Evaluating Specific Concept Erasure from Text-to-Image Generative Models
by: Fuchi, Masane, et al.
Published: (2025)
by: Fuchi, Masane, et al.
Published: (2025)
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation
by: Zhang, Yuhui, et al.
Published: (2023)
by: Zhang, Yuhui, et al.
Published: (2023)
Medical Image Synthesis via Fine-Grained Image-Text Alignment and Anatomy-Pathology Prompting
by: Chen, Wenting, et al.
Published: (2024)
by: Chen, Wenting, et al.
Published: (2024)
LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?
by: Wang, Yuchi, et al.
Published: (2024)
by: Wang, Yuchi, et al.
Published: (2024)
Pre-Trained Model Recommendation for Downstream Fine-tuning
by: Bai, Jiameng, et al.
Published: (2024)
by: Bai, Jiameng, et al.
Published: (2024)
In-Situ Tweedie Discrete Diffusion Models
by: Li, Xiao, et al.
Published: (2025)
by: Li, Xiao, et al.
Published: (2025)
Re-Thinking the Automatic Evaluation of Image-Text Alignment in Text-to-Image Models
by: Zhang, Huixuan, et al.
Published: (2025)
by: Zhang, Huixuan, et al.
Published: (2025)
Multimodal LLMs as Customized Reward Models for Text-to-Image Generation
by: Zhou, Shijie, et al.
Published: (2025)
by: Zhou, Shijie, et al.
Published: (2025)
Structured Captions Improve Prompt Adherence in Text-to-Image Models (Re-LAION-Caption 19M)
by: Merchant, Nicholas, et al.
Published: (2025)
by: Merchant, Nicholas, et al.
Published: (2025)
Test-Time Matching: Unlocking Compositional Reasoning in Multimodal Models
by: Zhu, Yinglun, et al.
Published: (2025)
by: Zhu, Yinglun, et al.
Published: (2025)
Preserving Pre-trained Representation Space: On Effectiveness of Prefix-tuning for Large Multi-modal Models
by: Kim, Donghoon, et al.
Published: (2024)
by: Kim, Donghoon, et al.
Published: (2024)
Teaching Text-to-Image Models to Communicate in Dialog
by: Sun, Xiaowen, et al.
Published: (2023)
by: Sun, Xiaowen, et al.
Published: (2023)
Similar Items
-
TMPDiff: Temporal Mixed-Precision for Diffusion Models
by: Lewandowski, Basile, et al.
Published: (2026) -
Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation
by: Yuan, Huizhuo, et al.
Published: (2024) -
CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching
by: Jiang, Dongzhi, et al.
Published: (2024) -
MPQ-Diff: Mixed Precision Quantization for Diffusion Models
by: Maruzzelli, Rocco Manz, et al.
Published: (2024) -
Efficient Model Editing with Task-Localized Sparse Fine-tuning
by: Iurada, Leonardo, et al.
Published: (2025)