Diffusion Model Fine-Tuning

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19 papers in the last four weeks, against 2 the four weeks before. 0.2% of all new papers.

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GramSR: Visual Feature Conditioning for Diffusion-Based Super-Resolution
Apr 28, 2026Fabio D'Oronzio, Federico Putamorsi, Leonardo Zini +2Diffusion Models for Image Restoration Diffusion Model Fine-Tuning
University of Modena and Reggio Emilia, Italy
Learning Illumination Control in Diffusion Models
Apr 27, 2026Nishit Anand, Manan Suri, Christopher Metzler +2Diffusion Model Fine-Tuning Image Relighting
University of Maryland College Park
Edit Where You Mean: Region-Aware Adapter Injection for Mask-Free Local Image Editing
Apr 26, 2026Honghao Cai, Xiangyuan Wang, Yunhao Bai +8Diffusion Transformer Text-Guided Image Editing
The Chinese University of Hong Kong, Shenzhen · Xiaohongshu Inc. · Peking University +2
DiffNR: Diffusion-Enhanced Neural Representation Optimization for Sparse-View 3D Tomographic Reconstruction
Apr 23, 2026Shiyan Su, Ruyi Zha, Danli Shi +2Diffusion Models for Image Restoration Sparse-View CT Reconstruction
1Monash University · 2The Australian National University · 3Hong Kong Polytechnic University
Optimizing Diffusion Priors in Image Reconstruction from a Single Observation
Apr 22, 2026Frederic Wang, Katherine L. BoumanBayesian Inverse Problems Image Reconstruction
Caltech, Pasadena CA 91125, USA
Projected Gradient Unlearning for Text-to-Image Diffusion Models: Defending Against Concept Revival Attacks
Apr 22, 2026Aljalila Aladawi, Mohammed Talha Alam, Fakhri KarrayDiffusion Model Fine-Tuning Diffusion Model Unlearning
Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE. · University of Waterloo, Ontario, Canada.
Learning to Credit the Right Steps: Objective-aware Process Optimization for Visual Generation
Apr 21, 2026Rui Li, Ke Hao, Yuanzhi Liang +4Multi-Objective Reinforcement Learning Video Diffusion Models
University of Science and Technology of China HeFei, China · Shanghai Jiao Tong University ShangHai, China · TeleAI ShangHai, China
$R^2$ -dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
Apr 21, 2026Zhenbang Du, Kejing Xia, Xinrui Zhong +6Diffusion Language Model Inference Diffusion Model Fine-Tuning
Georgia Institute of Technology · NVIDIA
Class-specific diffusion models improve military object detection in a low-data domain
Apr 20, 2026Ella P. Fokkinga, Jan Erik van Woerden, Thijs A. Eker +4Synthetic Data Augmentation Diffusion Model Guidance
TNO - Intelligent Imaging, Oude Waalsdorperweg 63, the Hague, the Netherlands
Reward Score Matching: Unifying Reward-based Fine-tuning for Flow and Diffusion Models
Apr 19, 2026Jeongjae Lee, Jinho Chang, Jeongsol Kim +1Diffusion Model Alignment Diffusion Model Fine-Tuning
Graduate School of AI KAIST, Korea
TeMuDance: Contrastive Alignment-Based Textual Control for Music-Driven Dance Generation
Apr 18, 2026Xinran Liu, Diptesh Kanojia, Wenwu Wang +1Text-to-Motion Generation Cross-Modal Alignment
University of Surrey, Guildford, Surrey, UK · 2Jiangnan University, Wuxi, Jiangsu, China
LeapAlign: Post-Training Flow Matching Models at Any Generation Step by Building Two-Step Trajectories
Apr 16, 2026Zhanhao Liang, Tao Yang, Jie Wu +2Diffusion Model Alignment Flow Matching
1The Australian National University · 2ByteDance Seed
Pretrained Video Models as Differentiable Physics Simulators for Urban Wind Flows
Mar 22, 2026Janne Perini, Rafael Bischof, Moab Arar +4Video Diffusion Models PDE Surrogate Modeling
1Computational Design Lab, ETH Zurich, Switzerland · 2Tel Aviv University, Israel · 3Architecture and Building Systems, ETH Zurich, Switzerland +2
SHIFT: Motion Alignment in Video Diffusion Models with Adversarial Hybrid Fine-Tuning
Mar 18, 2026Xi Ye, Wenjia Yang, Yangyang Xu +4Diffusion Model Alignment Video Diffusion Models
Tsinghua University · Ant Group · University of Chinese Academy of Sciences
Selective Fine-Tuning for Targeted and Robust Concept Unlearning
Feb 8, 2026Mansi, Avinash Kori, Francesca Toni +1Fine-Tuning Adversarial Robustness
Department of Computing Imperial College London, United Kingdom
Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design
Feb 4, 2026Jaemoo Choi, Yuchen Zhu, Wei Guo +6T2I Generation Diffusion Model Fine-Tuning
Georgia Institute of Technology · National University of Singapore · Nanjing university.
Mechanism Shift During Post-training from Autoregressive to Masked Diffusion Language Models
Jan 21, 2026Injin Kong, Hyoungjoon Lee, Yohan JoMasked Diffusion Models Autoregressive Diffusion
Graduate School of Data Science, Seoul National University · Department of Biosystems & Biomaterials Science and Engineering, Seoul National University
Direct Diffusion Score Preference Optimization via Stepwise Contrastive Policy-Pair Supervision
Dec 29, 2025Dohyun Kim, Seungwoo Lyu, Seung Wook Kim +1Diffusion Model Alignment Diffusion Model Fine-Tuning
Dept. of CSE, Korea University · 2NVIDIA
MixFlow Training: Alleviating Exposure Bias with Slowed Interpolation Mixture
Dec 22, 2025Hui Li, Fu-Yun Wang, Haoyuan Xia +4Diffusion Model Fine-Tuning Diffusion-Based Image Generation
Shanghai Innovation Institute · Fudan University · Shanghai Academy of AI for Science +2
Anchor to Expand: Semantic Anchoring for Personalized Text-to-Image Diffusion Models
Nov 27, 2025Seoyun Yang, Gihoon Kim, Taesup KimSubject-Driven Image Generation T2I Generation
Graduate School of Data Science, Seoul National University
Rethinking Garment Conditioning in Diffusion-based Virtual Try-On: Decouple, Don't Denoise
Nov 24, 2025Kihyun Na, Jinyoung Choi, Injung KimVirtual Try-On Diffusion Model Fine-Tuning
Advanced AI Talent Education and Research Group for Industrial Innovation, Handong Global University, Pohang 37554, Republic of Korea · Department of Artificial Intelligence, Computer and Electrical Engineering, Handong Global University, Pohang 37554, Republic of Korea
FeRA: Frequency-Energy Constrained Routing for Effective Diffusion Adaptation Fine-Tuning
Nov 22, 2025Bo Yin, Xiaobin Hu, Xingyu Zhou +7Fine-Tuning Adaptive Model Routing
National University of Singapore · University of Electronic Science and Technology of China · Nanyang Technological University +4
DC-Gen: Post-Training Diffusion Acceleration with Deeply Compressed Latent Space
Sep 29, 2025Wenkun He, Yuchao Gu, Junyu Chen +11Diffusion Model Fine-Tuning Diffusion Model Inference Acceleration
Anatomy-Grounded Weakly Supervised Prompt Tuning for Chest X-ray Latent Diffusion Models
Jun 12, 2025Konstantinos Vilouras, Ilias Stogiannidis, Junyu Yan +2Diffusion Model Alignment Prompt Tuning
School of Engineering, University of Edinburgh · Canon Medical Research Europe Ltd.
From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control
Feb 4, 2025Peiyan Hu, Xiaowei Qian, Wenhao Deng +8Diffusion Model Guidance Safety-Critical Control
Work done as an intern at Westlake University · Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China · School of Engineering, Westlake University, Hangzhou, China +2
C-DiffSET: Leveraging Latent Diffusion for SAR-to-EO Image Translation with Confidence-Guided Reliable Object Generation
Nov 16, 2024Jeonghyeok Do, Jaehyup Lee, Munchurl KimImage-to-Image Translation Latent Diffusion Models
KAIST · KNU

Apr 28, 2026, cs.CVJ/K move · Enter open · S save

GramSR: Visual Feature Conditioning for Diffusion-Based Super-Resolution

Fabio D'Oronzio, Federico Putamorsi, Leonardo Zini, Marcella Cornia+1

University of Modena and Reggio Emilia, Italy

Diffusion Models for Image Restoration Diffusion Model Fine-Tuning Conditional Diffusion Models Image Super-Resolution

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Despite recent advances, single-image super-resolution (SR) remains challenging, especially in real-world scenarios with complex degradations. Diffusion-based SR methods, particularly those built on Stable Diffusion, leverage strong generative priors but commonly rely on text conditioning derived from semantic captioning. Such textual descriptions provide only high-level semantics and lack the spatially aligned visual information required for faithful restoration, leading to a representation gap between abstract semantics and spatially aligned visual details. To address this limitation, we propose GramSR, a one-step diffusion-based SR framework that replaces text conditioning with dense visual features extracted from the low-resolution input using a pre-trained DINOv3 encoder. GramSR adopts a three-stage LoRA architecture, where pixel-level, semantic-level, and texture-level LoRA modules are trained sequentially. The pixel-level module focuses on degradation removal using

\ell_2

loss, the semantic-level module enhances perceptual details via LPIPS and CSD losses, and the texture-level module enforces feature correlation consistency through a Gram matrix loss computed from DINOv3 features. At inference, independent guidance scales enable flexible control over degradation removal, semantic enhancement, and texture preservation. Extensive experiments on standard SR benchmarks demonstrate that GramSR consistently outperforms existing one-step diffusion-based methods, achieving superior structural fidelity and texture realism. The code for this work is available at: https://github.com/aimagelab/GramSR.

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Latest papers 116