3 papers
cs.CV2026
Direct Diffusion Score Preference Optimization via Stepwise Contrastive Policy-Pair Supervision
Dohyun Kim, Seungwoo Lyu, Seung Wook Kim +1
Diffusion models have achieved impressive results in generative tasks such as text-to-image synthesis, yet they often struggle to fully align outputs with nuanced user intent and m…
cs.CV2025
Dynamic VLM-Guided Negative Prompting for Diffusion Models
Hoyeon Chang, Seungjin Kim, Yoonseok Choi
We propose a novel approach for dynamic negative prompting in diffusion models that leverages Vision-Language Models (VLMs) to adaptively generate negative prompts during the denoi…
cs.LG2025
Random Conditioning with Distillation for Data-Efficient Diffusion Model Compression
Dohyun Kim, Sehwan Park, Geonhee Han +2
Diffusion models generate high-quality images through progressive denoising but are computationally intensive due to large model sizes and repeated sampling. Knowledge distillation…