Cover Image

Directly Fine-Tuning Diffusion Models on Differentiable Rewards

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Clark, Kevin, Vicol, Paul, Swersky, Kevin, Fleet, David J
Format:	Preprint
Published:	2023
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

Video models are zero-shot learners and reasoners
by: Wiedemer, Thaddäus, et al.
Published: (2025)

AugLoss: A Robust Augmentation-based Fine Tuning Methodology
by: Otstot, Kyle, et al.
Published: (2022)

Greedy Growing Enables High-Resolution Pixel-Based Diffusion Models
by: Vasconcelos, Cristina N., et al.
Published: (2024)

Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models
by: Zhang, Xinxi, et al.
Published: (2024)

Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models
by: Shirkavand, Reza, et al.
Published: (2024)

Do generative video models understand physical principles?
by: Motamed, Saman, et al.
Published: (2025)

A Personalized Video-Based Hand Taxonomy: Application for Individuals with Spinal Cord Injury
by: Dousty, Mehdy, et al.
Published: (2024)

CRAFT: Aligning Diffusion Models with Fine-Tuning Is Easier Than You Think
by: Sun, Zening, et al.
Published: (2026)

VARD: Efficient and Dense Fine-Tuning for Diffusion Models with Value-based RL
by: Dai, Fengyuan, et al.
Published: (2025)

Reward Score Matching: Unifying Reward-based Fine-tuning for Flow and Diffusion Models
by: Lee, Jeongjae, et al.
Published: (2026)

Towards Understanding Multimodal Fine-Tuning: Spatial Features
by: Naghashyar, Lachin, et al.
Published: (2026)

Data-Efficient Ensemble Weather Forecasting with Diffusion Models
by: Valencia, Kevin, et al.
Published: (2025)

One Step Diffusion via Shortcut Models
by: Frans, Kevin, et al.
Published: (2024)

When Are Concepts Erased From Diffusion Models?
by: Lu, Kevin, et al.
Published: (2025)

Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization
by: Fan, Jiajun, et al.
Published: (2025)

Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model
by: Yang, Kai, et al.
Published: (2023)

Contrastive Learning to Fine-Tune Feature Extraction Models for the Visual Cortex
by: Mulrooney, Alex, et al.
Published: (2024)

CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference
by: Shekarforoush, Shayan, et al.
Published: (2024)

Diffusion-DRF: Free, Rich, and Differentiable Reward for Video Diffusion Fine-Tuning
by: Wang, Yifan, et al.
Published: (2026)

Directional Gradient Projection for Robust Fine-Tuning of Foundation Models
by: Huang, Chengyue, et al.
Published: (2025)

Policy-based Tuning of Autoregressive Image Models with Instance- and Distribution-Level Rewards
by: Baran, Orhun Buğra, et al.
Published: (2026)

On the Robustness Tradeoff in Fine-Tuning
by: Li, Kunyang, et al.
Published: (2025)

Diffusing Differentiable Representations
by: Savani, Yash, et al.
Published: (2024)

Task-Specific Directions: Definition, Exploration, and Utilization in Parameter Efficient Fine-Tuning
by: Si, Chongjie, et al.
Published: (2024)

Diffusion Reward: Learning Rewards via Conditional Video Diffusion
by: Huang, Tao, et al.
Published: (2023)

Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting
by: Zhong, Jincheng, et al.
Published: (2024)

Efficient and Versatile Robust Fine-Tuning of Zero-shot Models
by: Kim, Sungyeon, et al.
Published: (2024)

DP-RDM: Adapting Diffusion Models to Private Domains Without Fine-Tuning
by: Lebensold, Jonathan, et al.
Published: (2024)

Risks When Sharing LoRA Fine-Tuned Diffusion Model Weights
by: Yao, Dixi
Published: (2024)

Personalized Preference Fine-tuning of Diffusion Models
by: Dang, Meihua, et al.
Published: (2025)

Beyond Pairwise Preferences: Listwise Reward-Aware Alignment for Diffusion Models
by: Wang, Austin, et al.
Published: (2026)

Aligning Few-Step Diffusion Models with Dense Reward Difference Learning
by: Zhang, Ziyi, et al.
Published: (2024)

GDRO: Group-level Reward Post-training Suitable for Diffusion Models
by: Wang, Yiyang, et al.
Published: (2026)

ParetoSlider: Diffusion Models Post-Training for Continuous Reward Control
by: Golan, Shelly, et al.
Published: (2026)

Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
by: Shi, Jiang-Xin, et al.
Published: (2023)

FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models
by: Zheng, Weiying, et al.
Published: (2025)

Rethinking Fine-Tuning: Unlocking Hidden Capabilities in Vision-Language Models
by: Zhang, Mingyuan, et al.
Published: (2025)

Half-order Fine-Tuning for Diffusion Model: A Recursive Likelihood Ratio Optimizer
by: Ren, Tao, et al.
Published: (2025)

RobustNeRF: Ignoring Distractors with Robust Losses
by: Sabour, Sara, et al.
Published: (2023)

Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation
by: Yuan, Huizhuo, et al.
Published: (2024)