6 papers
PreferThinker: Reasoning-based Personalized Image Preference Assessment
Shengqi Xu, Xinpeng Zhou, Yabo Zhang +6
Personalized image preference assessment aims to evaluate an individual user's image preferences by relying only on a small set of reference images as prior information. Existing m…
Pareto-Guided Optimal Transport for Multi-Reward Alignment
Ying Ba, Tianyu Zhang, Mohan Zhou +5
Text-to-image generation models have achieved remarkable progress in preference optimization, yet achieving robust alignment across diverse reward models remains a significant chal…
Premier: Personalized Preference Modulation with Learnable User Embedding in Text-to-Image Generation
Zihao Wang, Yuxiang Wei, Xinpeng Zhou +5
Text-to-image generation has advanced rapidly, yet it still struggles to capture the nuanced user preferences. Existing approaches typically rely on multimodal large language model…
PrefGen: Multimodal Preference Learning for Preference-Conditioned Image Generation
Wenyi Mo, Tianyu Zhang, Yalong Bai +3
Preference-conditioned image generation seeks to adapt generative models to individual users, producing outputs that reflect personal aesthetic choices beyond the given textual pro…
Learning User Preferences for Image Generation Model
Wenyi Mo, Ying Ba, Tianyu Zhang +2
User preference prediction requires a comprehensive and accurate understanding of individual tastes. This includes both surface-level attributes, such as color and style, and deepe…
V2Flow: Unifying Visual Tokenization and Large Language Model Vocabularies for Autoregressive Image Generation
Guiwei Zhang, Tianyu Zhang, Mohan Zhou +2
We propose V2Flow, a novel tokenizer that produces discrete visual tokens capable of high-fidelity reconstruction, while ensuring structural and latent distribution alignment with…