LARGE LANGUAGE MODEL ARTIFICIAL INTELLIGENCE TEXT EVALUATION SYSTEM

Relevance scores may be determined based on text included in a document. The text may be divided into a text portions, with the relevance scores being determined based on a comparison of a text portion of the plurality of text portions with a criterion specified in natural language. A subset of the...

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Hauptverfasser: Blake, Ethan, Arredondo, Pablo, O'Kelly, Brian, DeFoor, Walter, Walker, Ryan, Qadrud-Din, Javed, deLevie, Alan
Format: Patent
Sprache:eng
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Zusammenfassung:Relevance scores may be determined based on text included in a document. The text may be divided into a text portions, with the relevance scores being determined based on a comparison of a text portion of the plurality of text portions with a criterion specified in natural language. A subset of the plurality of text portions may be selected based on the plurality of relevance scores, with each of the subset of the plurality of text portions having a relevance score surpassing a threshold. A criteria evaluation prompt may be sent to a remote text generation modeling system via a communication interface. The criteria evaluation prompts may include an instruction to evaluate one or more of the subset of text portions against the criterion.