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 |
Files in This Item:
File | Description | Size | Format | |
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SYM-AM-24-188.pdf | Student Poster | 473.77 kB | Adobe PDF | View/Open |
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