Artificial Intelligence #llm evaluation#drift detection
New Method Resolves Drift Attribution Ambiguity in LLM Evaluation Pipelines
A research paper introduces an anytime-valid attribution method for LLM evaluation pipelines that resolves the ambiguity between product drift and judge model changes. Using a fixed human-labeled anchor set and betting e-processes, the method achieved zero misattribution on silent version bumps and correctly attributed prompt changes in 110 of 120 runs, while the industry-default rolling z-test false-alarmed on 75% of drift-free streams.
Jun 16, 2026 1 source