3 papers
cs.CV2026
DivRL: Disentangled Self-Similarity Rewards for Diverse Subject-Driven Generation
Qian Wang, Zhenyu Li, Abdelrahman Eldesokey +1
Subject-driven image generation faces an "Identity-Diversity Paradox", where strong identity preservation often leads to rigid and low-diversity outputs. We propose a post-training…
cs.CR2026
When Safe Concepts Become Unsafe: Multi-Concept Compositional Vulnerabilities in Text-to-Image Models
Chaoshuo Zhang, Yibo Liang, Mengke Tian +7
Text-to-image (T2I) models are increasingly optimized for following user instructions faithfully. However, we find that this capability introduces a safety vulnerability we call Mu…
cs.CV2026
RL-RIG: A Generative Spatial Reasoner via Intrinsic Reflection
Tianyu Wang, Zhiyuan Ma, Qian Wang +3
Recent advancements in image generation have achieved impressive results in producing high-quality images. However, existing image generation models still generally struggle with a…