🧪 Test?View on arXiv
To Keep or Not to Keep: Learning KV Cache Retention in Disaggregated LLM Serving Systems
Not provided in the content
cache managementdisaggregated systemsLLM servingcost-aware optimization
2610.28637
Builder Relevance
2h ago80%
Abstract
This paper presents KVLearn, a framework for cost-aware KV-cache retention in disaggregated LLM serving systems, improving efficiency in cache management.
Reality Card
Core Claim
KVLearn reduces end-to-end time-to-first-token by up to 56% compared to No-Cache and significantly decreases inter-node KV transfer volume.
Method / Result
KVLearn reduces end-to-end time-to-first-token by up to 56% versus No-Cache.
Limitations
The paper does not specify the authors or provide detailed reproducibility information.
Paper to code
Verified implementation resources so builders can test the paper’s claims instead of stopping at the abstract.
No verified implementation link has been attached yet. AIBuzzHub will keep this panel separate from unverified search results.