Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/5078
Title: Evaluating SBIR Proposals: A Comparative Analysis using Artificial Intelligence and Statistical Programming in the DoD Acquisitions Process
Authors: Cullen Tores
Keywords: Student Poster
Issue Date: 29-May-2024
Publisher: Acquisition Research Program
Citation: Published--Unlimited Distribution
Series/Report no.: Acquisition Management;SYM-AM-24-188
Abstract: Assessment of Large Language Models’ (LLM) ability to automate classification of acquisition proposals as either competitive or noncompetitive. •This classification aims to establish a faster, more consistent, and objective evaluation system when compared to human assessment. •Three different prompt engineering strategies were used and compared against one another. •Interaction with the LLM was conducted via R programming and OpenAI application programming interface—not the standard graphical user interface.
Description: Symposium Student Poster
URI: https://dair.nps.edu/handle/123456789/5078
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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