1. NLP TRANSFORMERS: ANALYSIS OF LLMS AND TRADITIONAL APPROACHES FOR ENHANCED TEXT SUMMARIZATION
- Author
-
Yunus Emre Işıkdemir
- Subjects
metin özetleme ,transformer ,doğal dil i̇şleme ,büyük dil modelleri ,derin öğrenme ,text summarization ,transformers ,nlp ,llm ,deep learning ,Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
As the amount of the available information continues to grow, finding the relevant information has become increasingly challenging. As a solution, text summarization has emerged as a vital method for extracting essential information from lengthy documents. There are various techniques available for filtering documents and extracting the pertinent information. In this study, a comparative analysis is conducted to evaluate traditional approaches and state-of-the-art methods on the BBC News and CNN/DailyMail datasets. This study offers valuable insights for researchers to advance their research and helps practitioners in selecting the most suitable techniques for their specific use cases.
- Published
- 2024
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