Cover Image

Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gao, Weizhi, Hou, Zhichao, Yin, Junqi, Wang, Feiyi, Peng, Linyu, Liu, Xiaorui
Format:	Preprint
Published:	2025
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

Accelerating Large-Scale Dataset Distillation via Exploration-Exploitation Optimization
by: Alahmadi, Muhammad J., et al.
Published: (2026)

Attention Frequency Modulation: Training-Free Spectral Modulation of Diffusion Cross-Attention
by: Oh, Seunghun, et al.
Published: (2026)

ProTransformer: Robustify Transformers via Plug-and-Play Paradigm
by: Hou, Zhichao, et al.
Published: (2024)

Exploring Magnitude Preservation and Rotation Modulation in Diffusion Transformers
by: Bill, Eric Tillman, et al.
Published: (2025)

PQD: Post-training Quantization for Efficient Diffusion Models
by: Ye, Jiaojiao, et al.
Published: (2024)

Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier
by: Tsaris, Aristeidis, et al.
Published: (2024)

RB-Modulation: Training-Free Personalization of Diffusion Models using Stochastic Optimal Control
by: Rout, Litu, et al.
Published: (2024)

SAIP: A Plug-and-Play Scale-adaptive Module in Diffusion-based Inverse Problems
by: Wang, Lingyu, et al.
Published: (2025)

A Unified Module for Accelerating STABLE-DIFFUSION: LCM-LORA
by: Thakur, Ayush, et al.
Published: (2024)

Progressive Compression with Universally Quantized Diffusion Models
by: Yang, Yibo, et al.
Published: (2024)

m2mKD: Module-to-Module Knowledge Distillation for Modular Transformers
by: Lo, Ka Man, et al.
Published: (2024)

MPQ-Diff: Mixed Precision Quantization for Diffusion Models
by: Maruzzelli, Rocco Manz, et al.
Published: (2024)

EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models
by: Liu, Xuewen, et al.
Published: (2024)

Balancing Multimodal Domain Generalization via Gradient Modulation and Projection
by: Li, Hongzhao, et al.
Published: (2026)

Gradient-Aligned Calibration for Post-Training Quantization of Diffusion Models
by: Hoang, Dung Anh, et al.
Published: (2026)

MARR: Module-Adaptive Residual Reconstruction for Low-Bit Post-Training Quantization
by: Su, Le, et al.
Published: (2026)

Concept-Centric Token Interpretation for Vector-Quantized Generative Models
by: Yang, Tianze, et al.
Published: (2025)

Post-training Quantization for Text-to-Image Diffusion Models with Progressive Calibration and Activation Relaxing
by: Tang, Siao, et al.
Published: (2023)

TMPQ-DM: Joint Timestep Reduction and Quantization Precision Selection for Efficient Diffusion Models
by: Sun, Haojun, et al.
Published: (2024)

Subtractive Modulative Network with Learnable Periodic Activations
by: Wang, Tiou, et al.
Published: (2026)

DGQ: Distribution-Aware Group Quantization for Text-to-Image Diffusion Models
by: Ryu, Hyogon, et al.
Published: (2025)

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models
by: Zeng, Qian, et al.
Published: (2025)

Q-Drift: Quantization-Aware Drift Correction for Diffusion Model Sampling
by: Ryu, Sooyoung, et al.
Published: (2026)

Convolutional Rectangular Attention Module
by: Nguyen, Hai-Vy, et al.
Published: (2025)

CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalization
by: Gao, Qi, et al.
Published: (2023)

CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language Models
by: Yin, Junbo, et al.
Published: (2025)

Trainable Fixed-Point Quantization for Deep Learning Acceleration on FPGAs
by: Dai, Dingyi, et al.
Published: (2024)

Semantic-Guided Generative Image Augmentation Method with Diffusion Models for Image Classification
by: Li, Bohan, et al.
Published: (2023)

TAP: A Token-Adaptive Predictor Framework for Training-Free Diffusion Acceleration
by: Zhu, Haowei, et al.
Published: (2026)

FW-GAN: Frequency-Driven Handwriting Synthesis with Wave-Modulated MLP Generator
by: Khoa, Huynh Tong Dang, et al.
Published: (2025)

Qua$^2$SeDiMo: Quantifiable Quantization Sensitivity of Diffusion Models
by: Mills, Keith G., et al.
Published: (2024)

Token Caching for Diffusion Transformer Acceleration
by: Lou, Jinming, et al.
Published: (2024)

Edge Attention Module for Object Classification
by: Roy, Santanu, et al.
Published: (2025)

TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models
by: Huang, Yushi, et al.
Published: (2023)

SQ-DM: Accelerating Diffusion Models with Aggressive Quantization and Temporal Sparsity
by: Fan, Zichen, et al.
Published: (2025)

RespoDiff: Dual-Module Bottleneck Transformation for Responsible & Faithful T2I Generation
by: Sreelatha, Silpa Vadakkeeveetil, et al.
Published: (2025)

LAPA: Log-Domain Prediction-Driven Dynamic Sparsity Accelerator for Transformer Model
by: Wang, Huizheng, et al.
Published: (2025)

Accelerating Diffusion Models for Inverse Problems through Shortcut Sampling
by: Liu, Gongye, et al.
Published: (2023)

SpecDiff: Accelerating Diffusion Model Inference with Self-Speculation
by: Pan, Jiayi, et al.
Published: (2025)

Data Pruning in Generative Diffusion Models
by: Briq, Rania, et al.
Published: (2024)