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VAR-Q: Tuning-free KV Cache Quantization for Visual Autoregressive Image and Video Generation
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quantizationvisual generationautoregressivememory optimization
2611.05380
Builder Relevance
2h ago80%
Abstract
VAR-Q proposes a tuning-free KV-cache quantization framework that significantly reduces memory usage in visual autoregressive generation while maintaining quality.
Reality Card
Core Claim
VAR-Q achieves up to 78.5% reduction in KV memory usage with negligible quality degradation, enabling 6x larger inference batches.
Method / Result
Cuts KV memory by up to 78.5% across nine models.
Limitations
The paper does not specify authors or detailed experimental setups, which may hinder reproducibility.
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