VQRAE: Representation Quantization Autoencoders for Multimodal Understanding, Generation and Reconstruction
Summary
VQRAE introduces a unified visual tokenizer that can simultaneously support high-level multimodal understanding and discrete-token image generation. Building on a pretrained vision encoder and a high-dimensional semantic VQ codebook, it yields continuous semantic features for reasoning and discrete tokens for reconstruction, showing that quantizing semantic encoders with large codebooks can preserve both meaning and detail.
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