{"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/structured-content-preservation-for","title":"Structured Content Preservation for Unsupervised Text Style Transfer","arxiv_id":"1810.06526","date":"2018-10-15","proceeding":null,"authors":["Youzhi Tian","Zhiting Hu","Zhou Yu"],"abstract":"Text style transfer aims to modify the style of a sentence while keeping its\ncontent unchanged. Recent style transfer systems often fail to faithfully\npreserve the content after changing the style. This paper proposes a structured\ncontent preserving model that leverages linguistic information in the\nstructured fine-grained supervisions to better preserve the style-independent\ncontent during style transfer. In particular, we achieve the goal by devising\nrich model objectives based on both the sentence's lexical information and a\nlanguage model that conditions on content. The resulting model therefore is\nencouraged to retain the semantic meaning of the target sentences. We perform\nextensive experiments that compare our model to other existing approaches in\nthe tasks of sentiment and political slant transfer. Our model achieves\nsignificant improvement in terms of both content preservation and style\ntransfer in automatic and human evaluation.","url_abs":"http://arxiv.org/abs/1810.06526v2","url_pdf":"http://arxiv.org/pdf/1810.06526v2.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":"structured-content-preservation-for","repo_url":"https://github.com/YouzhiTian/Structured-Content-Preservation-for-Unsupervised-Text-Style-Transfer","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"structured-content-preservation-for","repo_url":"https://github.com/asyml/texar/tree/master/examples/text_style_transfer","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"style-transfer","task_name":"Style Transfer"},{"task_slug":"text-style-transfoer","task_name":"Text Style Transfer"},{"task_slug":"unsupervised-text-style-transfer","task_name":"Unsupervised Text Style Transfer"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1810.06526","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1810.06526"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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