HeadGuard: Selective Head Protection for Low-Bit VLM KV-Cache Quantization
Balancing memory efficiency and visual accuracy through selective precision masking for VLMs.
Low-bit key-value (KV) cache quantization saves storage but can sharply degrade vision-language model (VLM) accuracy. We introduce HeadGuard, a composable head-protection method that augments a base KV-cache quantizer with a fixed high-precision mask. Image-sensitivity and output...
ArXiv CS.LG
Source
Generated insight by OnAirToday AI
HeadGuard addresses the critical bottleneck of information loss in vision-language models when compressing memory during complex visual reasoning tasks. By selectively preserving high-precision data for sensitive attention heads, this approach enables significant hardware efficiency without sacrificing multimodal intelligence.
Comments
Keep comments relevant and respectful. No links, advertising, self-promotion, or spam.