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of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction" 4.1 State-of-the-art image generation; 4.2 Power-law scaling laws; 4.3 Zero-shot task generalization; 4.4 Ablation Study; 5 Future Work; 6 Conclusion; A Token.
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Source: dhumaloir.pages.dev Scaling LargeScale Generative MixtureofExpert Multimodal Model With VLMoE DeepSpeed , 🔥 Introducing VAR: a new paradigm in autoregressive visual generation : Visual Autoregressive Modeling (VAR) redefines the autoregressive learning on images as coarse-to-fine "next-scale prediction" or "next-resolution prediction", diverging from the standard raster-scan "next-token prediction". We present Visual AutoRegressive modeling (VAR), a new generation paradigm that redefines the autoregressive learning on images as coarse-to-fine "next.
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Paper Review Visual Autoregressive Modeling Scalable Image Generation via NextScale . We present Visual AutoRegressive modeling (VAR), a new generation paradigm that redefines the autoregressive learning on images as coarse-to-fine "next. 3 Method 3.1 Preliminary: autoregressive modeling via next-token prediction
Paper Review Visual Autoregressive Modeling Scalable Image Generation via NextScale Prediction . The VAR framework reconceptualizes the autoregressive modeling on images by shifting from next-token prediction to next-scale prediction approach, a process under which instead of being a single token, the autoregressive unit is an entire token map. We present Visual AutoRegressive modeling (VAR), a new generation paradigm that redefines the autoregressive learning on images as coarse-to-fine "next-scale prediction" or "next-resolution prediction", diverging from the standard raster-scan "next-token prediction".
