Risk-Constrained Freshness-Aware Semantic Caching for Open-Web Retrieval-Augmented LLMs
Semantic caching reduces the latency and cost of retrieval-augmented generation (RAG) by serving cached answers to semantically similar queries, but most existing methods do not model the time-varying freshness of open-web evidence. We present FreshCache, a three-tier semantic cache that treats cache reuse as a risk-constrained temporal inference problem: before approving a cache hit, FreshCache estimates the probability that the cached result is stale using a fitted exponential decay model enhanced by a learned MLP, and approves reuse only when that probability falls below a per-tier error budget across answers (epsilon = 0.10), URL lists (epsilon = 0.20), and page content (epsilon = 0.3...
| Authors | Muhammad Mansoor, Tahir Ahmad, Yeo-Chan Yoon |
|---|---|
| Primary category | cs.CL |
| Published | 5 July 2026 |
| Last updated at source | 5 July 2026 |
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