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From Generation to Scoring: Scaling LLM-Based Semantic Labeling at LinkedIn

Sheng, Jian et al.
arXiv (All) · Papers
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and-cluster-computingdistributedinformation-retrievalmachine-learningparallel
For efficiency, industrial large language model (LLM) labelers often pack many candidate labels into one prompt and generate a YES/NO answer for each, even when each decision depends only on the entity and one candidate. Generating these independent decisions as one answer list couples them, spends
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