Leveraging Faithfulness in Abstractive Text Summarization with Elementary Discourse Units
Abstractive text summarization uses the summarizer's own words to capture the main information of a source document in a summary. While it is more challenging to automate than extractive text summarization, recent advancements in deep learning approaches and pre-trained language models have im...
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| Format: | Article |
| Language: | English |
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LibraryPress@UF
2025-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/138888 |
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| author | Narjes Delpisheh Yllias Chali |
| author_facet | Narjes Delpisheh Yllias Chali |
| author_sort | Narjes Delpisheh |
| collection | DOAJ |
| description |
Abstractive text summarization uses the summarizer's own words to capture the main information of a source document in a summary. While it is more challenging to automate than extractive text summarization, recent advancements in deep learning approaches and pre-trained language models have improved its performance. However, abstractive text summarization still has issues such as hallucination and unfaithfulness. To address these problems, we propose a new approach that utilizes important Elementary Discourse Units (EDUs) to guide BART-based text summarization. We compare our approach with some previous approaches that have improved the faithfulness of the summary. Our approach was compared and tested on the CNN/Daily Mail dataset and showed an improvement in truthfulness and source document coverage.
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| format | Article |
| id | doaj-art-c947e7d01b0e428b964642efcd5489e7 |
| institution | DOAJ |
| issn | 2334-0754 2334-0762 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | LibraryPress@UF |
| record_format | Article |
| series | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| spelling | doaj-art-c947e7d01b0e428b964642efcd5489e72025-08-20T03:10:27ZengLibraryPress@UFProceedings of the International Florida Artificial Intelligence Research Society Conference2334-07542334-07622025-05-0138110.32473/flairs.38.1.138888Leveraging Faithfulness in Abstractive Text Summarization with Elementary Discourse UnitsNarjes DelpishehYllias Chali0University of Lethbridge Abstractive text summarization uses the summarizer's own words to capture the main information of a source document in a summary. While it is more challenging to automate than extractive text summarization, recent advancements in deep learning approaches and pre-trained language models have improved its performance. However, abstractive text summarization still has issues such as hallucination and unfaithfulness. To address these problems, we propose a new approach that utilizes important Elementary Discourse Units (EDUs) to guide BART-based text summarization. We compare our approach with some previous approaches that have improved the faithfulness of the summary. Our approach was compared and tested on the CNN/Daily Mail dataset and showed an improvement in truthfulness and source document coverage. https://journals.flvc.org/FLAIRS/article/view/138888 |
| spellingShingle | Narjes Delpisheh Yllias Chali Leveraging Faithfulness in Abstractive Text Summarization with Elementary Discourse Units Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| title | Leveraging Faithfulness in Abstractive Text Summarization with Elementary Discourse Units |
| title_full | Leveraging Faithfulness in Abstractive Text Summarization with Elementary Discourse Units |
| title_fullStr | Leveraging Faithfulness in Abstractive Text Summarization with Elementary Discourse Units |
| title_full_unstemmed | Leveraging Faithfulness in Abstractive Text Summarization with Elementary Discourse Units |
| title_short | Leveraging Faithfulness in Abstractive Text Summarization with Elementary Discourse Units |
| title_sort | leveraging faithfulness in abstractive text summarization with elementary discourse units |
| url | https://journals.flvc.org/FLAIRS/article/view/138888 |
| work_keys_str_mv | AT narjesdelpisheh leveragingfaithfulnessinabstractivetextsummarizationwithelementarydiscourseunits AT ylliaschali leveragingfaithfulnessinabstractivetextsummarizationwithelementarydiscourseunits |