{"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/recent-trends-in-deep-learning-based-natural","title":"Recent Trends in Deep Learning Based Natural Language Processing","arxiv_id":"1708.02709","date":"2017-08-09","proceeding":null,"authors":["Tom Young","Devamanyu Hazarika","Soujanya Poria","Erik Cambria"],"abstract":"Deep learning methods employ multiple processing layers to learn hierarchical\nrepresentations of data and have produced state-of-the-art results in many\ndomains. Recently, a variety of model designs and methods have blossomed in the\ncontext of natural language processing (NLP). In this paper, we review\nsignificant deep learning related models and methods that have been employed\nfor numerous NLP tasks and provide a walk-through of their evolution. We also\nsummarize, compare and contrast the various models and put forward a detailed\nunderstanding of the past, present and future of deep learning in NLP.","url_abs":"http://arxiv.org/abs/1708.02709v8","url_pdf":"http://arxiv.org/pdf/1708.02709v8.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":"recent-trends-in-deep-learning-based-natural","repo_url":"https://github.com/GallupGovt/multivac","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"recent-trends-in-deep-learning-based-natural","repo_url":"https://github.com/anuragreddygv323/Important-stuff","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"recent-trends-in-deep-learning-based-natural","repo_url":"https://github.com/ridakadri14/AspectBasedSentimentAnalysis","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1708.02709","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}