{"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/a-neural-attention-model-for-abstractive","title":"A Neural Attention Model for Abstractive Sentence Summarization","arxiv_id":"1509.00685","date":"2015-09-02","proceeding":"EMNLP 2015 9","authors":["Alexander M. Rush","Sumit Chopra","Jason Weston"],"abstract":"Summarization based on text extraction is inherently limited, but\ngeneration-style abstractive methods have proven challenging to build. In this\nwork, we propose a fully data-driven approach to abstractive sentence\nsummarization. Our method utilizes a local attention-based model that generates\neach word of the summary conditioned on the input sentence. While the model is\nstructurally simple, it can easily be trained end-to-end and scales to a large\namount of training data. The model shows significant performance gains on the\nDUC-2004 shared task compared with several strong baselines.","url_abs":"http://arxiv.org/abs/1509.00685v2","url_pdf":"http://arxiv.org/pdf/1509.00685v2.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":[{"paper_slug":"a-neural-attention-model-for-abstractive","repo_url":"https://github.com/Ganeshpadmanaban/Neural-Attention-Model","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"a-neural-attention-model-for-abstractive","repo_url":"https://github.com/Ganeshpadmanaban/Neural-Attention-Model-Abstractive-Summarization","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"a-neural-attention-model-for-abstractive","repo_url":"https://github.com/tensorflow/models/tree/master/research/textsum","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"a-neural-attention-model-for-abstractive","repo_url":"https://github.com/toru34/rush_emnlp_2015","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"extractive-document-summarization","task_name":"Extractive Text Summarization"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"sentence-summarization","task_name":"Sentence Summarization"},{"task_slug":"text-summarization","task_name":"Text Summarization"},{"task_slug":"model","task_name":"model"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/extractive-text-summarization-on-duc-2004","task":"Extractive Text Summarization","dataset":"DUC 2004 Task 1","model":"Abs","rank_in_archive_order":1,"of":1,"metrics":{"ROUGE-1":"26.55","ROUGE-2":"7.06","ROUGE-L":"22.05"},"uses_additional_data":false},{"leaderboard":"/sota/text-summarization-on-duc-2004-task-1","task":"Text Summarization","dataset":"DUC 2004 Task 1","model":"Abs+","rank_in_archive_order":11,"of":13,"metrics":{"ROUGE-1":"28.18","ROUGE-2":"8.49","ROUGE-L":"23.81"},"uses_additional_data":false},{"leaderboard":"/sota/text-summarization-on-duc-2004-task-1","task":"Text Summarization","dataset":"DUC 2004 Task 1","model":"ABS","rank_in_archive_order":13,"of":13,"metrics":{"ROUGE-L":"22.05"},"uses_additional_data":false},{"leaderboard":"/sota/text-summarization-on-gigaword","task":"Text Summarization","dataset":"GigaWord","model":"Abs+","rank_in_archive_order":39,"of":41,"metrics":{"ROUGE-1":"31"},"uses_additional_data":false},{"leaderboard":"/sota/text-summarization-on-gigaword","task":"Text Summarization","dataset":"GigaWord","model":"Abs","rank_in_archive_order":40,"of":41,"metrics":{"ROUGE-1":"30.88"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1509.00685","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}