Cover Image

Accelerating Diffusion Models with One-to-Many Knowledge Distillation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Linfeng, Ma, Kaisheng
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers
by: Liu, Jiacheng, et al.
Published: (2025)

DisCa: Accelerating Video Diffusion Transformers with Distillation-Compatible Learnable Feature Caching
by: Zou, Chang, et al.
Published: (2026)

Decouple-Then-Merge: Finetune Diffusion Models as Multi-Task Learning
by: Ma, Qianli, et al.
Published: (2024)

Orchestrate Latent Expertise: Advancing Online Continual Learning with Multi-Level Supervision and Reverse Self-Distillation
by: Yan, HongWei, et al.
Published: (2024)

Accelerating Diffusion Transformers with Token-wise Feature Caching
by: Zou, Chang, et al.
Published: (2024)

Towards Effective Data-Free Knowledge Distillation via Diverse Diffusion Augmentation
by: Li, Muquan, et al.
Published: (2024)

Teacher-Guided One-Shot Pruning via Context-Aware Knowledge Distillation
by: Alim, Md. Samiul, et al.
Published: (2025)

LIFT and PLACE: A Simple, Stable, and Effective Knowledge Distillation Framework for Lightweight Diffusion Models
by: Han, Hyunsoo, et al.
Published: (2026)

Heterogeneous Generative Knowledge Distillation with Masked Image Modeling
by: Wang, Ziming, et al.
Published: (2023)

DKDM: Data-Free Knowledge Distillation for Diffusion Models with Any Architecture
by: Xiang, Qianlong, et al.
Published: (2024)

Inference-Time Diffusion Model Distillation
by: Park, Geon Yeong, et al.
Published: (2024)

Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation
by: Zhou, Mingyuan, et al.
Published: (2024)

Progressive Knowledge Distillation Of Stable Diffusion XL Using Layer Level Loss
by: Gupta, Yatharth, et al.
Published: (2024)

Accelerating Diffusion-based Video Editing via Heterogeneous Caching: Beyond Full Computing at Sampled Denoising Timestep
by: Liu, Tianyi, et al.
Published: (2026)

UV-Attack: Physical-World Adversarial Attacks for Person Detection via Dynamic-NeRF-based UV Mapping
by: Li, Yanjie, et al.
Published: (2025)

Not All Samples Should Be Utilized Equally: Towards Understanding and Improving Dataset Distillation
by: Wang, Shaobo, et al.
Published: (2024)

SpeCa: Accelerating Diffusion Transformers with Speculative Feature Caching
by: Liu, Jiacheng, et al.
Published: (2025)

Look One and More: Distilling Hybrid Order Relational Knowledge for Cross-Resolution Image Recognition
by: Ge, Shiming, et al.
Published: (2024)

TernaryCLIP: Efficiently Compressing Vision-Language Models with Ternary Weights and Distilled Knowledge
by: Zhang, Shu-Hao, et al.
Published: (2025)

DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models
by: Wang, Qichao, et al.
Published: (2026)

Adaptive Explicit Knowledge Transfer for Knowledge Distillation
by: Park, Hyungkeun, et al.
Published: (2024)

AnimateDiff-Lightning: Cross-Model Diffusion Distillation
by: Lin, Shanchuan, et al.
Published: (2024)

Rethinking Token-wise Feature Caching: Accelerating Diffusion Transformers with Dual Feature Caching
by: Zou, Chang, et al.
Published: (2024)

SnapFlow: One-Step Action Generation for Flow-Matching VLAs via Progressive Self-Distillation
by: Luan, Wuyang, et al.
Published: (2026)

FreqCa: Accelerating Diffusion Models via Frequency-Aware Caching
by: Liu, Jiacheng, et al.
Published: (2025)

CacheQuant: Comprehensively Accelerated Diffusion Models
by: Liu, Xuewen, et al.
Published: (2025)

Di$\mathtt{[M]}$O: Distilling Masked Diffusion Models into One-step Generator
by: Zhu, Yuanzhi, et al.
Published: (2025)

Distilling Cross-Modal Knowledge via Feature Disentanglement
by: Liu, Junhong, et al.
Published: (2025)

Multi-student Diffusion Distillation for Better One-step Generators
by: Song, Yanke, et al.
Published: (2024)

One-Step Diffusion Distillation through Score Implicit Matching
by: Luo, Weijian, et al.
Published: (2024)

Forecasting When to Forecast: Accelerating Diffusion Models with Confidence-Gated Taylor
by: Guan, Xiaoliu, et al.
Published: (2025)

HybridStitch: Pixel and Timestep Level Model Stitching for Diffusion Acceleration
by: Sun, Desen, et al.
Published: (2026)

From Structure to Detail: Hierarchical Distillation for Efficient Diffusion Model
by: Cheng, Hanbo, et al.
Published: (2025)

GVD: Guiding Video Diffusion Model for Scalable Video Distillation
by: Li, Kunyang, et al.
Published: (2025)

Distilling Multi-view Diffusion Models into 3D Generators
by: Qin, Hao, et al.
Published: (2025)

Understanding the Role of the Projector in Knowledge Distillation
by: Miles, Roy, et al.
Published: (2023)

MorphDistill: Distilling Unified Morphological Knowledge from Pathology Foundation Models for Colorectal Cancer Survival Prediction
by: Khan, Hikmat, et al.
Published: (2026)

ViT-Linearizer: Distilling Quadratic Knowledge into Linear-Time Vision Models
by: Wei, Guoyizhe, et al.
Published: (2025)

MoVE-KD: Knowledge Distillation for VLMs with Mixture of Visual Encoders
by: Cao, Jiajun, et al.
Published: (2025)

Data Upcycling Knowledge Distillation for Image Super-Resolution
by: Zhang, Yun, et al.
Published: (2023)