TGV-KV: Text-Grounded KV Eviction for Vision-Language Models 事件

TGV-KV: Text-Grounded KV Eviction for Vision-Language Models arXiv:2606.03075v1 Announce Type: new Abstract: Vision-Language Models (VLMs) inherit the auto-regressive generation paradigm and cache the keys and values (KV) of all previous tokens to accelerate inference, resulting in memory consumption that scales linearly with context length. This issue is particularly pronounced in VLMs due to substantial redundancy in the visual modality. Although KV cache eviction approaches can effectively r