Factorized Vector Quantization
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- Factorized Vector Quantization Advances Discrete Visual Tokens
A new arXiv paper proposes Factorized Vector Quantization for discrete visual representations, using complementary fixed-dimensional views and symmetric parallel codebooks to reduce saturation as bit budgets increase. Its authors report that the resulting model matches continuous visual representations on multimodal understanding and outperforms UniAR and Emu3-Chat by 22.8% and 59.2%, respectively, on a nine-metric average. The paper also claims competitiveness with continuous-representation models such as Qwen3-VL, including on fine-grained OCR tasks.
Hugging Face · Papers · 🔥 0
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