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PolarQuant: Leveraging Polar Transformation for Efficient Key Cache Quantization and Decoding Acceleration

arXiv:2502.00527v2 Announce Type: replace Abstract: The KV cache in large language models is a dominant factor in memory usage, limiting their broader applicability. Quantizing the cache to lower bit widths is an effective way to reduce computational costs; however, previous methods struggle with quantizing key vectors due to outliers, resulting in excessive overhead. We propose a novel quantization approach called PolarQuant, which efficiently addresses the outlier challenge.

arXiv CS 2d ago