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cs.CV2026
Improving Sample Diversity in Autoregressive Text-to-Image Generation via Cluster Truncation
Trang Nguyen, Shuang Wu, Runyan Tan +1
While diffusion models achieve state-of-the-art image quality for text-to-image (T2I) generation, recent work has demonstrated that they suffer from sample diversity collapse. In t…
cs.CV2026
Dream-VL & Dream-VLA: Open Vision-Language and Vision-Language-Action Models with Diffusion Language Model Backbone
Jiacheng Ye, Shansan Gong, Jiahui Gao +6
While autoregressive Large Vision-Language Models (VLMs) have achieved remarkable success, their sequential generation often limits their efficacy in complex visual planning and dy…