3 papers
cs.CV2026
Relational Feature Caching for Accelerating Diffusion Transformers
Byunggwan Son, Jeimin Jeon, Jeongwoo Choi +1
Feature caching approaches accelerate diffusion transformers (DiTs) by storing the output features of computationally expensive modules at certain timesteps, and exploiting them fo…
cs.CV2025
AccuQuant: Simulating Multiple Denoising Steps for Quantizing Diffusion Models
Seunghoon Lee, Jeongwoo Choi, Byunggwan Son +3
We present in this paper a novel post-training quantization (PTQ) method, dubbed AccuQuant, for diffusion models. We show analytically and empirically that quantization errors for…
cs.CV2024
FYI: Flip Your Images for Dataset Distillation
Byunggwan Son, Youngmin Oh, Donghyeon Baek +1
Dataset distillation synthesizes a small set of images from a large-scale real dataset such that synthetic and real images share similar behavioral properties (e.g, distributions o…