{"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/seq2seq-vis-a-visual-debugging-tool-for","title":"Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models","arxiv_id":"1804.09299","date":"2018-04-25","proceeding":null,"authors":["Hendrik Strobelt","Sebastian Gehrmann","Michael Behrisch","Adam Perer","Hanspeter Pfister","Alexander M. Rush"],"abstract":"Neural Sequence-to-Sequence models have proven to be accurate and robust for\nmany sequence prediction tasks, and have become the standard approach for\nautomatic translation of text. The models work in a five stage blackbox process\nthat involves encoding a source sequence to a vector space and then decoding\nout to a new target sequence. This process is now standard, but like many deep\nlearning methods remains quite difficult to understand or debug. In this work,\nwe present a visual analysis tool that allows interaction with a trained\nsequence-to-sequence model through each stage of the translation process. The\naim is to identify which patterns have been learned and to detect model errors.\nWe demonstrate the utility of our tool through several real-world large-scale\nsequence-to-sequence use cases.","url_abs":"http://arxiv.org/abs/1804.09299v2","url_pdf":"http://arxiv.org/pdf/1804.09299v2.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":"seq2seq-vis-a-visual-debugging-tool-for","repo_url":"https://github.com/HendrikStrobelt/Seq2Seq-Vis","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1804.09299","atlas_url":"https://app.syntology.ai/?focus=1804.09299","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}