{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/document-summarization-with-text-segmentation","title":"Document Summarization with Text Segmentation","arxiv_id":"2301.08817","date":"2023-01-20","proceeding":null,"authors":["Lesly Miculicich","Benjamin Han"],"abstract":"In this paper, we exploit the innate document segment structure for improving the extractive summarization task. We build two text segmentation models and find the most optimal strategy to introduce their output predictions in an extractive summarization model. Experimental results on a corpus of scientific articles show that extractive summarization benefits from using a highly accurate segmentation method. In particular, most of the improvement is in documents where the most relevant information is not at the beginning thus, we conclude that segmentation helps in reducing the lead bias problem.","url_abs":"https://arxiv.org/abs/2301.08817v1","url_pdf":"https://arxiv.org/pdf/2301.08817v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"articles","task_name":"Articles"},{"task_slug":"document-summarization","task_name":"Document Summarization"},{"task_slug":"extractive-summarization","task_name":"Extractive Summarization"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"text-segmentation","task_name":"Text Segmentation"},{"task_slug":"text-summarization","task_name":"Text Summarization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/text-summarization-on-arxiv","task":"Text Summarization","dataset":"Arxiv HEP-TH citation graph","model":"ExtSum + oracle segmentation (extractive)","rank_in_archive_order":4,"of":28,"metrics":{"ROUGE-1":"49.49","ROUGE-2":"21.04","ROUGE-L":"44.34"},"uses_additional_data":false},{"leaderboard":"/sota/text-summarization-on-arxiv","task":"Text Summarization","dataset":"Arxiv HEP-TH citation graph","model":"ExtSum + supervised segmentation (extractive)","rank_in_archive_order":6,"of":28,"metrics":{"ROUGE-1":"49.11","ROUGE-2":"20.68","ROUGE-L":"44.01"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}