Masked transformer models for class-conditional image generation have become a
compelling alternative to diffusion models. Typically comprising two stages-an initial VQGAN …

Building on the foundations of language modeling in natural language processing, Next
Token Prediction (NTP) has evolved into a versatile training objective for machine learning …

連続値自己回帰 (AR) 画像生成モデルは, 離散トークンモデルと比較して顕著な優位性を示し,
優れた再構成品質と高い生成忠実度を実証している. しかしながら, 自己回帰フレームワークの計算 …

Image tokenizers form the foundation of modern text-to-image generative models but are
notoriously difficult to train. Furthermore, most existing text-to-image models rely on large …

We introduce RandAR, a decoder-only visual autoregressive (AR) model capable of
generating images in arbitrary token orders. Unlike previous decoder-only AR models that …

Autoregressive (AR) modeling has achieved remarkable success in natural language
processing by enabling models to generate text with coherence and contextual …

Efficient image tokenization with high compression ratios remains a critical challenge for
training generative models. We present SoftVQ-VAE, a continuous image tokenizer that …

Autoregressive (AR) models have achieved remarkable success in natural language and
image generation, but their application to 3D shape modeling remains largely unexplored …

Many-body systems at low temperature have revealed non-trivial phases of materials, such
as spin liquids, which have found applications in the evolving fields of superconductivity …