Mixing Importance with Diversity: Joint Optimization for KV Cache Compression in Large Vision-Language Models
融合重要性与多样性:KV缓存压缩的联合优化
机构 * EPIC Lab, Shanghai Jiao Tong University(上海交通大学) ; Sichuan University(四川大学) ; Huazhong University of Science and Technology(华中科技大学)
专题命中 视觉定位与Grounding :vision-language model(title,abstract);grounding(abstract);分类 cs.CV
AI总结 MixKV通过融合重要性与多样性,优化KV缓存压缩,提升多模态模型的存储效率与推理性能。
Comments Accepted by ICLR 2026. Our code is available at https://github.com/xuyang-liu16/MixKV