arXiv Artificial Intelligence

Exploring a Layer-Wise Design Space for KV Cache Eviction

Exploring a Layer-Wise Design Space for KV Cache Eviction

Quick summary

arXiv:2606.15157v2 Announce Type: replace-cross Abstract: KV cache eviction methods typically use a single retention-rule family throughout a model, making eviction-method identity a model-level design choice. Yet Transformer layers differ substantially in their attention behavior, representations, and sensitivity to compression, suggesting that a uniform rule may overlook useful layer-wise structure. This raises a basic question: should eviction methods themselves vary across layers? We investigate this question by composing existing eviction methods across Transformer layers and systematical

Key takeaways

  • arXiv:2606.15157v2 Announce Type: replace-cross Abstract: KV cache eviction methods typically use a single retention-rule family throughout a model, making eviction-method identity a model-level design choice.
  • Yet Transformer layers differ substantially in their attention behavior, representations, and sensitivity to compression, suggesting that a uniform rule may overlook useful layer-wise structure.
  • This raises a basic question: should eviction methods themselves vary across layers?

Why it matters

This model development creates a new option for users and a new testing obligation for developers. A fixed evaluation set comparing quality, cost and failure behavior is more useful than launch claims.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗