3 papers
cs.AI2026
RAE-AR: Taming Autoregressive Models with Representation Autoencoders
Hu Yu, Hang Xu, Jie Huang +4
The latent space of generative modeling is long dominated by the VAE encoder. The latents from the pretrained representation encoders (e.g., DINO, SigLIP, MAE) are previously consi…
cs.CV2025
Highly Efficient Test-Time Scaling for T2I Diffusion Models with Text Embedding Perturbation
Hang Xu, Linjiang Huang, Feng Zhao
Test-time scaling (TTS) aims to achieve better results by increasing random sampling and evaluating samples based on rules and metrics. However, in text-to-image(T2I) diffusion mod…
cs.CV2025
FR-TTS: Test-Time Scaling for NTP-based Image Generation with Effective Filling-based Reward Signal
Hang Xu, Linjiang Huang, Feng Zhao
Test-time scaling (TTS) has become a prevalent technique in image generation, significantly boosting output quality by expanding the number of parallel samples and filtering them u…