Year: 2023
Type: dissertation
Abstract: This project evaluates the performance of generative models of summarization in aviation safety domain. Models such as DaVinci, Text-DaVinci-003, and GPT-3.5-Turbo were analyzed in both their zero-shot learning and fine-tuned performance against state-of-the-art models. In zero-shot learning, generative models were superior in most cases to the state-of-the- art models, whereas the fine-tuned models could learn with less information about the dataset. These results predict promising advances in the summarization space to address current limitations in the field.
Author: Queipo, Laura
Institution: Massachusetts Institute of Technology
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7047165481