Enhancing Text Summarization: Evaluating Transformer-Based Models and the Role of Large Language Models like ChatGPT - Savci, Pinar; Das, Bihter (Institute of Electrical and Electronics Engineers Inc., 2023)
In today's world, as a substantial amount of textual data is generated, processing and summarizing this data in a meaningful way has become a significant research area. Text summarization aims to extract concise and informative summaries from textual data. In this study, the performance of transformer-based models in text summarization is evaluated by comparing them with human-generated summaries. Additionally, the utility of large language models like ChatGPT in the field of summarization is investigated. The study presents detailed insights into the summarization performance of transformer-based models such as BART and T5, aiming to guide future research in summarization. © 2023 IEEE.
4th International Informatics and Software Engineering Conference, IISEC 2023 -- 21 December 2023 through 22 December 2023 -- Ankara -- 196814
Keywords: BART; Gpt-2; Pegasus; pre-Trained language models; summarization; T5