{"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-level-neural-machine-translation","title":"Document-Level Neural Machine Translation with Hierarchical Attention Networks","arxiv_id":"1809.01576","date":"2018-09-05","proceeding":"EMNLP 2018 10","authors":["Lesly Miculicich","Dhananjay Ram","Nikolaos Pappas","James Henderson"],"abstract":"Neural Machine Translation (NMT) can be improved by including document-level\ncontextual information. For this purpose, we propose a hierarchical attention\nmodel to capture the context in a structured and dynamic manner. The model is\nintegrated in the original NMT architecture as another level of abstraction,\nconditioning on the NMT model's own previous hidden states. Experiments show\nthat hierarchical attention significantly improves the BLEU score over a strong\nNMT baseline with the state-of-the-art in context-aware methods, and that both\nthe encoder and decoder benefit from context in complementary ways.","url_abs":"http://arxiv.org/abs/1809.01576v2","url_pdf":"http://arxiv.org/pdf/1809.01576v2.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":"document-level-neural-machine-translation","repo_url":"https://github.com/idiap/HAN_NMT","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"GPL-3.0"}},{"paper_slug":"document-level-neural-machine-translation","repo_url":"https://github.com/Nick-Zhao-Engr/Machine-Translation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"nmt","task_name":"NMT"},{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1809.01576","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}