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README.md

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 **MeissonFlow Research** is a non-commercial research group dedicated to advancing generative modeling techniques for structured visual and multimodal content creation. 
 We aim to design models and algorithms that help creators produce high-quality content with greater efficiency and control.
 
-Our journey began with [**MaskGIT**](https://arxiv.org/abs/2202.04200), a pioneering work by [**Huiwen Chang**](https://scholar.google.com/citations?hl=en&user=eZQNcvcAAAAJ), which introduced a bidirectional transformer decoder for image synthesis—outperforming traditional raster-scan autoregressive (AR) generation.
+Our journey began with [**MaskGIT**](https://arxiv.org/abs/2202.04200), a pioneering work by [**Huiwen Chang**](https://scholar.google.com/citations?hl=en&user=eZQNcvcAAAAJ), which introduced a bidirectional transformer decoder for image synthesis and outperformed traditional raster-scan autoregressive (AR) generation.
 This paradigm was later extended to text-to-image synthesis in [**MUSE**](https://arxiv.org/abs/2301.00704).
 
 Building upon these foundations, we scaled masked generative modeling with the latest architectural designs and sampling strategies, culminating in [**Monetico** and **Meissonic**](https://github.com/viiika/Meissonic) built from scratch, which are on par with leading diffusion models such as SDXL while maintaining greater efficiency.