Advanced Generative AI Methods for Academic Text Summarization
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The exponential growth of scientific literature emphasizes the need for employing advanced techniques for effective text summarization, which can significantly speed up the research process. This study tackles the challenge by advancing scientific text summarization through AI and deep learning methods. We delve into the integration and fine-tuning of cutting-edge models, including LED-Large, Pegasus variants, and BART, aiming to refine the summarization process. Unique combinations, such as SciBERT with LED-Large, were investigated to ensure the capture of critical details frequently missed by traditional methods. This novel approach led to notable improvements in summarization effectiveness. Our findings indicate that models like LED-Large excel in quickly adapting to training data, achieving impressive semantic understanding with fewer training epochs, evidenced by achieving a FRES score of 28.5852 and ROUGE scores, including a ROUGE-l F1-Score of 0.4991. However, while extensively trained models like BART -large and Pegasus displayed strong semantic capabilities, they also pointed to the necessity for refinements in readability and higher-order n-gram overlap in the produced summaries. © 2024 IEEE.
Açıklama
Anahtar Kelimeler
BART, Cosine Similarity, Deep Learning, LED-Large, Literature Review Generation, Natural Language Processing, Pegasus-Large, SciBERT, Scientific Summarization, Transformers
Kaynak
2024 IEEE 3rd International Conference on Computing and Machine Intelligence, ICMI 2024 - Proceedings
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Dar, Z., Raheel, M., Bokhari, U., Jamil, A., Alazawi, E. M., & Hameed, A. A. (2024, April). Advanced Generative AI Methods for Academic Text Summarization. In 2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI) (pp. 1-7). IEEE.
