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Исследования2026年10月8日
From High Recall to High Utility: Dataset-Adaptive Post-Processing of LLM-Generated Customer Intents
Large language models can extract useful signals from heterogeneous enterprise data, but high-recall extraction often produces outputs that are duplicated, uneven in granularity, semantically overlapping, or too numerous for downstream systems and human reviewers to use…
Mahesh Viswanathan, Joan Rossello, Leticia Fernandes, Paul Mutawe·arXiv — cs.AI
Original SourceKey Takeaways
- 01.Large language models can extract useful signals from heterogeneous enterprise data, but high-recall extraction often produces outputs that are duplicated, uneven in granularity, semantically overlapping, or too numerous for downstream systems and human reviewers to use…
This material is provided as an extended analytical summary.
Read full article at sourceAggregated within AI Qazaqstan national intelligence stream with author attribution.
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