5 papers
VAR RL Done Right: Tackling Asynchronous Policy Conflicts in Visual Autoregressive Generation
Shikun Sun, Liao Qu, Huichao Zhang +8
Visual generation is dominated by three paradigms: AutoRegressive (AR), diffusion, and Visual AutoRegressive (VAR) models. Unlike AR and diffusion, VARs operate on heterogeneous in…
NextFlow: Unified Sequential Modeling Activates Multimodal Understanding and Generation
Huichao Zhang, Liao Qu, Yiheng Liu +33
We present NextFlow, a unified decoder-only autoregressive transformer trained on 6 trillion interleaved text-image discrete tokens. By leveraging a unified vision representation w…
DetailFlow: 1D Coarse-to-Fine Autoregressive Image Generation via Next-Detail Prediction
Yiheng Liu, Liao Qu, Huichao Zhang +10
This paper presents DetailFlow, a coarse-to-fine 1D autoregressive (AR) image generation method that models images through a novel next-detail prediction strategy. By learning a re…
TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation
Liao Qu, Huichao Zhang, Yiheng Liu +7
We present TokenFlow, a novel unified image tokenizer that bridges the long-standing gap between multimodal understanding and generation. Prior research attempt to employ a single…
XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation
Bowen Chen, Mengyi Zhao, Haomiao Sun +4
Achieving fine-grained control over subject identity and semantic attributes (pose, style, lighting) in text-to-image generation, particularly for multiple subjects, often undermin…