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cs.CV2026

TreeAdapter: Hierarchical Taxonomy-Guided Adapter Composition for Fine-Grained Species Image Generation

Yuze Sun, Zhongjie Duan, Yingda Chen

Although general text-to-image models excel in open-domain generation, their performance degrades significantly in specialized downstream domains, particularly when generating imag…

cs.CV2026

Compressing Image Style Training into a Single Model Forward

Zhongjie Duan, Yingda Chen

Diffusion-based style transfer must balance inference efficiency with stylization fidelity. Adapter-based methods are efficient, but they inject style as an external condition and…

cs.CV2026

VIRAL: Visual In-Context Reasoning via Analogy in Diffusion Transformers

Zhiwen Li, Zhongjie Duan, Jinyan Ye +4

Replicating In-Context Learning (ICL) in computer vision remains challenging due to task heterogeneity. We propose \textbf{VIRAL}, a framework that elicits visual reasoning from a…

cs.CV2025

Comprehensive Evaluation and Analysis for NSFW Concept Erasure in Text-to-Image Diffusion Models

Die Chen, Zhiwen Li, Cen Chen +5

Text-to-image diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the strong generalization capabiliti…

cs.CV2025

AutoLoRA: Automatic LoRA Retrieval and Fine-Grained Gated Fusion for Text-to-Image Generation

Zhiwen Li, Zhongjie Duan, Die Chen +4

Despite recent advances in photorealistic image generation through large-scale models like FLUX and Stable Diffusion v3, the practical deployment of these architectures remains con…

cs.CV2024

ArtAug: Enhancing Text-to-Image Generation through Synthesis-Understanding Interaction

Zhongjie Duan, Qianyi Zhao, Cen Chen +4

The emergence of diffusion models has significantly advanced image synthesis. The recent studies of model interaction and self-corrective reasoning approach in large language model…