{"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/learning-disentangled-representations-of","title":"Learning Disentangled Representations of Texts with Application to Biomedical Abstracts","arxiv_id":"1804.07212","date":"2018-04-19","proceeding":"EMNLP 2018 10","authors":["Sarthak Jain","Edward Banner","Jan-Willem van de Meent","Iain J. Marshall","Byron C. Wallace"],"abstract":"We propose a method for learning disentangled representations of texts that\ncode for distinct and complementary aspects, with the aim of affording\nefficient model transfer and interpretability. To induce disentangled\nembeddings, we propose an adversarial objective based on the (dis)similarity\nbetween triplets of documents with respect to specific aspects. Our motivating\napplication is embedding biomedical abstracts describing clinical trials in a\nmanner that disentangles the populations, interventions, and outcomes in a\ngiven trial. We show that our method learns representations that encode these\nclinically salient aspects, and that these can be effectively used to perform\naspect-specific retrieval. We demonstrate that the approach generalizes beyond\nour motivating application in experiments on two multi-aspect review corpora.","url_abs":"http://arxiv.org/abs/1804.07212v2","url_pdf":"http://arxiv.org/pdf/1804.07212v2.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":"learning-disentangled-representations-of","repo_url":"https://github.com/successar/neural-nlp","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"retrieval","task_name":"Retrieval"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1804.07212","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}