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Prompt Chaining or Stepwise Prompt? Refinement in Text Summarization
Annual Meeting of the Association for Computational LinguisticsLarge language models (LLMs) have demonstrated the capacity to improve summary quality by mirroring a human-like iterative process of critique and refinement starting from the initial draft.
Shichao Sun +4 more
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Text Summarization Using Automatic Text Summarization
2025 9th International Conference on Computational System and Information Technology for Sustainable Solutions (CSITSS)The rapid emergence of multimedia technologies as well as the Internet saw a rise in the volumes of text data. Such huge amounts of text may give some insights that need to be properly distilled.
A. K. M, Shreyas S, Shreyas K
semanticscholar +1 more source
2015
Automated text summarization systems seek to provide the most important content contained in their (single or multiple document, and static or streaming over time) input. Extractive summarizers use various methods to assign an importance score to each fragment of the input and return the highest-scoring fragments, while abstractive summarizers attempt ...
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Automated text summarization systems seek to provide the most important content contained in their (single or multiple document, and static or streaming over time) input. Extractive summarizers use various methods to assign an importance score to each fragment of the input and return the highest-scoring fragments, while abstractive summarizers attempt ...
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Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services, 2009
Automated text summarization is important to for humans to better manage the massive information explosion. Several machine learning approaches could be successfully used to handle the problem. This paper reports the results of our study to compare the performance between neural networks and support vector machines for text summarization.
Keivan Kianmehr +7 more
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Automated text summarization is important to for humans to better manage the massive information explosion. Several machine learning approaches could be successfully used to handle the problem. This paper reports the results of our study to compare the performance between neural networks and support vector machines for text summarization.
Keivan Kianmehr +7 more
openaire +1 more source
2011
Automatic Text Summarization is a Natural Language Processing task which has experienced great development in recent years, mostly due to the rapid growth of the Internet. Therefore, we need methods and tools that help users to manage large amounts of information.
S. Soumya +3 more
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Automatic Text Summarization is a Natural Language Processing task which has experienced great development in recent years, mostly due to the rapid growth of the Internet. Therefore, we need methods and tools that help users to manage large amounts of information.
S. Soumya +3 more
openaire +1 more source
Topics in Language Disorders, 2010
Purpose: This article reviews the literature on students’ developing skills in summarizing expository texts and describes strategies for evaluating students’ expository summaries. Evaluation outcomes are presented for a professional development project aimed at helping teachers develop new techniques for teaching summarization.
Carol Westby +3 more
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Purpose: This article reviews the literature on students’ developing skills in summarizing expository texts and describes strategies for evaluating students’ expository summaries. Evaluation outcomes are presented for a professional development project aimed at helping teachers develop new techniques for teaching summarization.
Carol Westby +3 more
openaire +1 more source
2012
This article describes research and development on the automated creation of summaries of one or more texts. It defines the concept of summary and presents an overview of the principal approaches in summarization. It describes the design, implementation, and performance of various summarization systems.
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This article describes research and development on the automated creation of summaries of one or more texts. It defines the concept of summary and presents an overview of the principal approaches in summarization. It describes the design, implementation, and performance of various summarization systems.
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Information Processing Letters, 2018
Abstract Responsive text summarization (RTS) is an approach to web design aimed at allowing desktop web pages to be read in response to the size of the device a user is browsing with. RTS implements the TextRank algorithm, so it can be exploited to generate very short summaries (more apt for mobile devices, where screen space is at a premium) or ...
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Abstract Responsive text summarization (RTS) is an approach to web design aimed at allowing desktop web pages to be read in response to the size of the device a user is browsing with. RTS implements the TextRank algorithm, so it can be exploited to generate very short summaries (more apt for mobile devices, where screen space is at a premium) or ...
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Automatic text summarization: A comprehensive survey
Expert systems with applications, 2021Wafaa S. El-Kassas +3 more
semanticscholar +1 more source