{"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/incorporating-copying-mechanism-in-sequence","title":"Incorporating Copying Mechanism in Sequence-to-Sequence Learning","arxiv_id":"1603.06393","date":"2016-03-21","proceeding":"ACL 2016 8","authors":["Jiatao Gu","Zhengdong Lu","Hang Li","Victor O. K. Li"],"abstract":"We address an important problem in sequence-to-sequence (Seq2Seq) learning\nreferred to as copying, in which certain segments in the input sequence are\nselectively replicated in the output sequence. A similar phenomenon is\nobservable in human language communication. For example, humans tend to repeat\nentity names or even long phrases in conversation. The challenge with regard to\ncopying in Seq2Seq is that new machinery is needed to decide when to perform\nthe operation. In this paper, we incorporate copying into neural network-based\nSeq2Seq learning and propose a new model called CopyNet with encoder-decoder\nstructure. CopyNet can nicely integrate the regular way of word generation in\nthe decoder with the new copying mechanism which can choose sub-sequences in\nthe input sequence and put them at proper places in the output sequence. Our\nempirical study on both synthetic data sets and real world data sets\ndemonstrates the efficacy of CopyNet. For example, CopyNet can outperform\nregular RNN-based model with remarkable margins on text summarization tasks.","url_abs":"http://arxiv.org/abs/1603.06393v3","url_pdf":"http://arxiv.org/pdf/1603.06393v3.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":"incorporating-copying-mechanism-in-sequence","repo_url":"https://github.com/MseXing/CopyNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"incorporating-copying-mechanism-in-sequence","repo_url":"https://github.com/TellinaTool/nl2bash","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"GPL-3.0"}},{"paper_slug":"incorporating-copying-mechanism-in-sequence","repo_url":"https://github.com/adamklec/copynet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"incorporating-copying-mechanism-in-sequence","repo_url":"https://github.com/majumderb/sanskrit-ocr","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"incorporating-copying-mechanism-in-sequence","repo_url":"https://github.com/rizwan09/paper","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"incorporating-copying-mechanism-in-sequence","repo_url":"https://gitlab.com/ucdavisnlp/damd-multiwoz","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"incorporating-copying-mechanism-in-sequence","repo_url":"https://github.com/allenai/allennlp-models","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"text-summarization","task_name":"Text Summarization"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"seq2seq","method_name":"Seq2Seq"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1603.06393","atlas_url":"https://app.syntology.ai/?focus=1603.06393","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}