{"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/the-amu-uedin-submission-to-the-wmt16-news","title":"The AMU-UEDIN Submission to the WMT16 News Translation Task: Attention-based NMT Models as Feature Functions in Phrase-based SMT","arxiv_id":"1605.04809","date":"2016-05-16","proceeding":"WS 2016 8","authors":["Marcin Junczys-Dowmunt","Tomasz Dwojak","Rico Sennrich"],"abstract":"This paper describes the AMU-UEDIN submissions to the WMT 2016 shared task on\nnews translation. We explore methods of decode-time integration of\nattention-based neural translation models with phrase-based statistical machine\ntranslation. Efficient batch-algorithms for GPU-querying are proposed and\nimplemented. For English-Russian, our system stays behind the state-of-the-art\npure neural models in terms of BLEU. Among restricted systems, manual\nevaluation places it in the first cluster tied with the pure neural model. For\nthe Russian-English task, our submission achieves the top BLEU result,\noutperforming the best pure neural system by 1.1 BLEU points and our own\nphrase-based baseline by 1.6 BLEU. After manual evaluation, this system is the\nbest restricted system in its own cluster. In follow-up experiments we improve\nresults by additional 0.8 BLEU.","url_abs":"http://arxiv.org/abs/1605.04809v3","url_pdf":"http://arxiv.org/pdf/1605.04809v3.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":"the-amu-uedin-submission-to-the-wmt16-news","repo_url":"https://github.com/emjotde/mosesdecoder_nmt","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"LGPL-2.1"}}],"tasks":[{"task_slug":null,"task_name":"GPU"},{"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=1605.04809","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}