3 papers
cs.CV2026
Mixture of Style Experts for Diverse Image Stylization
Shihao Zhu, Ziheng Ouyang, Yijia Kang +5
Diffusion-based stylization has advanced significantly, yet existing methods are limited to color-driven transformations, neglecting complex semantics and material details. We intr…
cs.CL2025
SASQ: Static Activation Scaling for Quantization-Aware Training in Large Language Models
Shizhuo Mao, Song Chen, Yi Kang
Large language models (LLMs) excel at natural language tasks but face deployment challenges due to their growing size outpacing GPU memory advancements. Model quantization mitigate…
cs.CV2025
HQ-DM: Single Hadamard Transformation-Based Quantization-Aware Training for Low-Bit Diffusion Models
Shizhuo Mao, Hongtao Zou, Qihu Xie +2
Diffusion models have demonstrated significant applications in the field of image generation. However, their high computational and memory costs pose challenges for deployment. Mod…