Cover Image

Training-free Diffusion Model Alignment with Sampling Demons

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yeh, Po-Hung, Lee, Kuang-Huei, Chen, Jun-Cheng
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

EMC$^2$: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence
by: Yau, Chung-Yiu, et al.
Published: (2024)

Exposing Diversity Bias in Deep Generative Models: Statistical Origins and Correction of Diversity Error
by: Farnia, Farzan, et al.
Published: (2026)

Constrained Diffusion Models via Dual Training
by: Khalafi, Shervin, et al.
Published: (2024)

Identifying and Understanding Cross-Class Features in Adversarial Training
by: Wei, Zeming, et al.
Published: (2025)

LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders
by: Khodabandeh, Borna, et al.
Published: (2025)

Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup
by: Chidambaram, Muthu, et al.
Published: (2022)

Pattern based learning and optimisation through pricing for bin packing problem
by: Zhang, Huayan, et al.
Published: (2024)

Conjugate-Gradient-like Based Adaptive Moment Estimation Optimization Algorithm for Deep Learning
by: Tian, Jiawu, et al.
Published: (2024)

MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates
by: Mozaffari, Mohammad, et al.
Published: (2023)

Calibrated Adversarial Sampling: Multi-Armed Bandit-Guided Generalization Against Unforeseen Attacks
by: Wang, Rui, et al.
Published: (2025)

SMI: Statistical Membership Inference for Reliable Unlearned Model Auditing
by: Sun, Jialong, et al.
Published: (2026)

Unsupervised Training of Diffusion Models for Feasible Solution Generation in Neural Combinatorial Optimization
by: Hong, Seong-Hyun, et al.
Published: (2024)

Amortized Guidance for Image Inpainting with Pretrained Diffusion Models
by: Huang, Yilie, et al.
Published: (2026)

DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models
by: Saadati, Nastaran, et al.
Published: (2024)

Interpreting and Improving Diffusion Models from an Optimization Perspective
by: Permenter, Frank, et al.
Published: (2023)

Decentralized Personalized Federated Learning
by: Kharrat, Salma, et al.
Published: (2024)

Understanding Sampler Stochasticity in Training Diffusion Models for RLHF
by: Sheng, Jiayuan, et al.
Published: (2025)

Unsupervised Point Cloud Pre-Training via Contrasting and Clustering
by: Mei, Guofeng, et al.
Published: (2022)

Manifold-Guided Lyapunov Control with Diffusion Models
by: Mukherjee, Amartya, et al.
Published: (2024)

Alignment-Guided Score Matching for Text-to-Image Alignment in Diffusion Models
by: Lee, Jaa-Yeon, et al.
Published: (2026)

Learning Binary Sampling Patterns for Single-Pixel Imaging using Bilevel Optimisation
by: Tudosie, Serban Cristian, et al.
Published: (2025)

Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data
by: Aali, Asad, et al.
Published: (2024)

On Distributed Larger-Than-Memory Subset Selection With Pairwise Submodular Functions
by: Böther, Maximilian, et al.
Published: (2024)

FreeAugment: Data Augmentation Search Across All Degrees of Freedom
by: Bekor, Tom, et al.
Published: (2024)

Mean-Field Path-Integral Diffusion: From Samples to Interacting Agents
by: Chertkov, Michael
Published: (2026)

MatchDiffusion: Training-free Generation of Match-cuts
by: Pardo, Alejandro, et al.
Published: (2024)

EVODiff: Entropy-aware Variance Optimized Diffusion Inference
by: Li, Shigui, et al.
Published: (2025)

Low Rank Support Quaternion Matrix Machine
by: Chen, Wang, et al.
Published: (2025)

TAUE: Training-free Noise Transplant and Cultivation Diffusion Model
by: Nagai, Daichi, et al.
Published: (2025)

Diffusion Models without Classifier-free Guidance
by: Tang, Zhicong, et al.
Published: (2025)

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization
by: Lee, Dongyeun, et al.
Published: (2025)

Deep graph matching meets mixed-integer linear programming: Relax at your own risk ?
by: Xu, Zhoubo, et al.
Published: (2021)

ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule
by: Huang, Yilie, et al.
Published: (2026)

Spectral Motion Alignment for Video Motion Transfer using Diffusion Models
by: Park, Geon Yeong, et al.
Published: (2024)

OrthoFuse: Training-free Riemannian Fusion of Orthogonal Style-Concept Adapters for Diffusion Models
by: Aliev, Ali, et al.
Published: (2026)

Stitched Value Model for Diffusion Alignment
by: Go, Hyojun, et al.
Published: (2026)

Training-free Detection of AI-generated images via Cropping Robustness
by: Choi, Sungik, et al.
Published: (2025)

PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment
by: Lee, Suhyeon, et al.
Published: (2025)

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation
by: Monsefi, Amin Karimi, et al.
Published: (2025)

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm
by: Wang, Lujia, et al.
Published: (2023)