{"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/investigating-capsule-networks-with-dynamic","title":"Investigating Capsule Networks with Dynamic Routing for Text Classification","arxiv_id":"1804.00538","date":"2018-03-29","proceeding":"EMNLP 2018 10","authors":["Wei Zhao","Jianbo Ye","Min Yang","Zeyang Lei","Suofei Zhang","Zhou Zhao"],"abstract":"In this study, we explore capsule networks with dynamic routing for text\nclassification. We propose three strategies to stabilize the dynamic routing\nprocess to alleviate the disturbance of some noise capsules which may contain\n\"background\" information or have not been successfully trained. A series of\nexperiments are conducted with capsule networks on six text classification\nbenchmarks. Capsule networks achieve state of the art on 4 out of 6 datasets,\nwhich shows the effectiveness of capsule networks for text classification. We\nadditionally show that capsule networks exhibit significant improvement when\ntransfer single-label to multi-label text classification over strong baseline\nmethods. To the best of our knowledge, this is the first work that capsule\nnetworks have been empirically investigated for text modeling.","url_abs":"http://arxiv.org/abs/1804.00538v4","url_pdf":"http://arxiv.org/pdf/1804.00538v4.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":"investigating-capsule-networks-with-dynamic","repo_url":"https://github.com/andyweizhao/capsule_text_classification","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"investigating-capsule-networks-with-dynamic","repo_url":"https://github.com/abhishek-924/Capsule-Network","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"investigating-capsule-networks-with-dynamic","repo_url":"https://github.com/andyweizhao/capsule","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"investigating-capsule-networks-with-dynamic","repo_url":"https://github.com/kevindeangeli/capsuleNetwork","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"multi-label-text-classification","task_name":"Multi-Label Text Classification"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"},{"task_slug":"subjectivity-analysis","task_name":"Subjectivity Analysis"},{"task_slug":"text-classification","task_name":"Text Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/sentiment-analysis-on-cr","task":"Sentiment Analysis","dataset":"CR","model":"Capsule-B","rank_in_archive_order":8,"of":9,"metrics":{"Accuracy":"85.1"},"uses_additional_data":false},{"leaderboard":"/sota/sentiment-analysis-on-mr","task":"Sentiment Analysis","dataset":"MR","model":"Capsule-B","rank_in_archive_order":7,"of":19,"metrics":{"Accuracy":"82.3"},"uses_additional_data":false},{"leaderboard":"/sota/sentiment-analysis-on-sst-2-binary","task":"Sentiment Analysis","dataset":"SST-2 Binary classification","model":"Capsule-B","rank_in_archive_order":76,"of":87,"metrics":{"Accuracy":"86.8"},"uses_additional_data":false},{"leaderboard":"/sota/subjectivity-analysis-on-subj","task":"Subjectivity Analysis","dataset":"SUBJ","model":"Capsule-B","rank_in_archive_order":11,"of":19,"metrics":{"Accuracy":"93.8"},"uses_additional_data":false},{"leaderboard":"/sota/text-classification-on-ag-news","task":"Text Classification","dataset":"AG News","model":"Capsule-B","rank_in_archive_order":12,"of":24,"metrics":{"Error":"7.4"},"uses_additional_data":false},{"leaderboard":"/sota/text-classification-on-trec-6","task":"Text Classification","dataset":"TREC-6","model":"Capsule-B","rank_in_archive_order":15,"of":19,"metrics":{"Error":"7.2"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1804.00538","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}