{"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/ac-blstm-asymmetric-convolutional","title":"AC-BLSTM: Asymmetric Convolutional Bidirectional LSTM Networks for Text Classification","arxiv_id":"1611.01884","date":"2016-11-07","proceeding":null,"authors":["Depeng Liang","Yongdong Zhang"],"abstract":"Recently deeplearning models have been shown to be capable of making\nremarkable performance in sentences and documents classification tasks. In this\nwork, we propose a novel framework called AC-BLSTM for modeling sentences and\ndocuments, which combines the asymmetric convolution neural network (ACNN) with\nthe Bidirectional Long Short-Term Memory network (BLSTM). Experiment results\ndemonstrate that our model achieves state-of-the-art results on five tasks,\nincluding sentiment analysis, question type classification, and subjectivity\nclassification. In order to further improve the performance of AC-BLSTM, we\npropose a semi-supervised learning framework called G-AC-BLSTM for text\nclassification by combining the generative model with AC-BLSTM.","url_abs":"http://arxiv.org/abs/1611.01884v3","url_pdf":"http://arxiv.org/pdf/1611.01884v3.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":"ac-blstm-asymmetric-convolutional","repo_url":"https://github.com/Ldpe2G/AC-BLSTM","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"mxnet","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"sentence-embeddings","task_name":"Sentence Embeddings"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"},{"task_slug":"text-classification","task_name":"Text Classification"},{"task_slug":"text-classification-1","task_name":"text-classification"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"memory-network","method_name":"Memory Network"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}