{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T00:08:59Z","timestamp":1755907739114,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T00:00:00Z","timestamp":1702598400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Guangdong Basic and Applied Basic Research Foundation, China","award":["2021A1515012556"],"award-info":[{"award-number":["2021A1515012556"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,12,15]]},"DOI":"10.1145\/3639233.3639348","type":"proceedings-article","created":{"date-parts":[[2024,3,5]],"date-time":"2024-03-05T11:02:10Z","timestamp":1709636530000},"page":"44-50","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Leveraging Salience Analysis and Sparse Attention for Long Document Summarization"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4216-106X","authenticated-orcid":false,"given":"Zhihua","family":"Jiang","sequence":"first","affiliation":[{"name":"Department of Computer Science, Jinan University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4878-521X","authenticated-orcid":false,"given":"Yaxuan","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jinan University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6306-6811","authenticated-orcid":false,"given":"Dongning","family":"Rao","sequence":"additional","affiliation":[{"name":"School of Computer, Guangdong University of Technology, China"}]}],"member":"320","published-online":{"date-parts":[[2024,3,5]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Longformer: The Long-Document Transformer. CoRR abs\/2004.05150","author":"Beltagy Iz","year":"2020","unstructured":"Iz Beltagy, Matthew\u00a0E. Peters, and Arman Cohan. 2020. Longformer: The Long-Document Transformer. CoRR abs\/2004.05150 (2020)."},{"key":"e_1_3_2_1_2_1","volume-title":"Generating Long Sequences with Sparse Transformers. CoRR abs\/1904.10509","author":"Child Rewon","year":"2019","unstructured":"Rewon Child, Scott Gray, Alec Radford, and Ilya Sutskever. 2019. Generating Long Sequences with Sparse Transformers. CoRR abs\/1904.10509 (2019)."},{"volume-title":"NAACL-HLT (2)","author":"Cohan Arman","key":"e_1_3_2_1_3_1","unstructured":"Arman Cohan, Franck Dernoncourt, Doo\u00a0Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, and Nazli Goharian. 2018. A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents. In NAACL-HLT (2). Association for Computational Linguistics, 615\u2013621."},{"key":"e_1_3_2_1_4_1","volume-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019","volume":"1","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, Minneapolis, MN, USA, June 2-7, 2019, Volume 1 (Long and Short Papers), Jill Burstein, Christy Doran, and Thamar Solorio (Eds.). Association for Computational Linguistics, 4171\u20134186."},{"key":"e_1_3_2_1_5_1","volume-title":"LexRank: Graph-based Lexical Centrality as Salience in Text Summarization. CoRR abs\/1109.2128","author":"Erkan G\u00fcnes","year":"2011","unstructured":"G\u00fcnes Erkan and Dragomir\u00a0R. Radev. 2011. LexRank: Graph-based Lexical Centrality as Salience in Text Summarization. CoRR abs\/1109.2128 (2011)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2020.3037401"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.703"},{"key":"e_1_3_2_1_8_1","volume-title":"ROUGE: A Package for Automatic Evaluation of Summaries. In Text Summarization Branches Out","author":"Lin Chin-Yew","year":"2004","unstructured":"Chin-Yew Lin. 2004. ROUGE: A Package for Automatic Evaluation of Summaries. In Text Summarization Branches Out. Association for Computational Linguistics, Barcelona, Spain."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1230"},{"volume-title":"SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents","author":"Nallapati Ramesh","key":"e_1_3_2_1_10_1","unstructured":"Ramesh Nallapati, Feifei Zhai, and Bowen Zhou. 2017. SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents. In AAAI. AAAI Press, 3075\u20133081."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.590"},{"volume-title":"EMNLP (1)","author":"Pilault Jonathan","key":"e_1_3_2_1_12_1","unstructured":"Jonathan Pilault, Raymond Li, Sandeep Subramanian, and Chris Pal. 2020. On Extractive and Abstractive Neural Document Summarization with Transformer Language Models. In EMNLP (1). Association for Computational Linguistics, 9308\u20139319."},{"key":"e_1_3_2_1_13_1","unstructured":"Alec Radford and Karthik Narasimhan. 2018. Improving Language Understanding by Generative Pre-Training."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1410"},{"key":"e_1_3_2_1_15_1","volume-title":"Hierarchical Learning for Generation with Long Source Sequences. CoRR abs\/2104.07545","author":"Rohde Tobias","year":"2021","unstructured":"Tobias Rohde, Xiaoxia Wu, and Yinhan Liu. 2021. Hierarchical Learning for Generation with Long Source Sequences. CoRR abs\/2104.07545 (2021)."},{"volume-title":"ACL (1)","author":"Liu J.","key":"e_1_3_2_1_16_1","unstructured":"Abigail See, Peter\u00a0J. Liu, and Christopher\u00a0D. Manning. 2017. Get To The Point: Summarization with Pointer-Generator Networks. In ACL (1). Association for Computational Linguistics, 1073\u20131083."},{"key":"e_1_3_2_1_17_1","volume-title":"Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan\u00a0N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is All you Need. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna\u00a0M. Wallach, Rob Fergus, S.\u00a0V.\u00a0N. Vishwanathan, and Roman Garnett (Eds.). 5998\u20136008."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1298"},{"volume-title":"Systematically Exploring Redundancy Reduction in Summarizing Long Documents","author":"Xiao Wen","key":"e_1_3_2_1_19_1","unstructured":"Wen Xiao and Giuseppe Carenini. 2020. Systematically Exploring Redundancy Reduction in Summarizing Long Documents. In AACL\/IJCNLP. Association for Computational Linguistics, 516\u2013528."},{"key":"e_1_3_2_1_20_1","volume-title":"Big Bird: Transformers for Longer Sequences. In NeurIPS.","author":"Zaheer Manzil","year":"2020","unstructured":"Manzil Zaheer, Guru Guruganesh, Kumar\u00a0Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Onta\u00f1\u00f3n, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, and Amr Ahmed. 2020. Big Bird: Transformers for Longer Sequences. In NeurIPS."},{"key":"e_1_3_2_1_21_1","volume-title":"PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization. In ICML(Proceedings of Machine Learning Research, Vol.\u00a0119). PMLR, 11328\u201311339.","author":"Zhang Jingqing","year":"2020","unstructured":"Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter\u00a0J. Liu. 2020. PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization. In ICML(Proceedings of Machine Learning Research, Vol.\u00a0119). PMLR, 11328\u201311339."},{"key":"e_1_3_2_1_22_1","volume-title":"BERTScore: Evaluating Text Generation with BERT. In 8th International Conference on Learning Representations, ICLR 2020","author":"Zhang Tianyi","year":"2020","unstructured":"Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian\u00a0Q. Weinberger, and Yoav Artzi. 2020. BERTScore: Evaluating Text Generation with BERT. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net."}],"event":{"name":"NLPIR 2023: 2023 7th International Conference on Natural Language Processing and Information Retrieval","acronym":"NLPIR 2023","location":"Seoul Republic of Korea"},"container-title":["Proceedings of the 2023 7th International Conference on Natural Language Processing and Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3639233.3639348","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3639233.3639348","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T19:57:27Z","timestamp":1755892647000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3639233.3639348"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,15]]},"references-count":22,"alternative-id":["10.1145\/3639233.3639348","10.1145\/3639233"],"URL":"https:\/\/doi.org\/10.1145\/3639233.3639348","relation":{},"subject":[],"published":{"date-parts":[[2023,12,15]]},"assertion":[{"value":"2024-03-05","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}