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MIXAR: Scaling Autoregressive Pixel-based Language Models to Multiple Languages and Scripts
Pixel-based language models are gaining momentum as alternatives to traditional token-based approaches, promising to circumvent tokenization challenges; however, existing models remain English-centric and are hard to train as generators. This paper introduces MIXAR, the first generative multilingual
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