3 papers
cs.CV2025
LoRAverse: A Submodular Framework to Retrieve Diverse Adapters for Diffusion Models
Mert Sonmezer, Matthew Zheng, Pinar Yanardag
Low-rank Adaptation (LoRA) models have revolutionized the personalization of pre-trained diffusion models by enabling fine-tuning through low-rank, factorized weight matrices speci…
cs.CV2025
Personalized Image Editing in Text-to-Image Diffusion Models via Collaborative Direct Preference Optimization
Connor Dunlop, Matthew Zheng, Kavana Venkatesh +1
Text-to-image (T2I) diffusion models have made remarkable strides in generating and editing high-fidelity images from text. Yet, these models remain fundamentally generic, failing…
cs.CV2025
Stylebreeder: Exploring and Democratizing Artistic Styles through Text-to-Image Models
Matthew Zheng, Enis Simsar, Hidir Yesiltepe +3
Text-to-image models are becoming increasingly popular, revolutionizing the landscape of digital art creation by enabling highly detailed and creative visual content generation. Th…