Tune your threshold before adding an LLM judge: optimal escalation rate was 0%
Reasonable_Royal_621 · reddit · 2026-10-22
The CacheVerifier team tested the classic pattern — escalate "unsure" semantic-cache hits (verifier score near the threshold) to an LLM judge while auto-deciding the rest. Replaying on 3 public benchmarks produced a counterintuitive result:
- Against their default threshold, the escalation looked somewhat useful
- But once the single threshold was tuned to the actual cost ratio of a wrong hit vs. a miss, the optimal escalation rate was 0% in most settings — if a judge call costs 0.7x a cache miss, nothing ever escalated on any dataset
Fun side note: the judge rejected 60% of hits the benchmark labeled fine, and was sometimes right. The takeaway: tune your threshold to cost before adding a judge. Caveat: they only tested score distance, not ensembles. Repo linked (section 5.20).
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