{"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/recurrent-neural-network-for-text","title":"Recurrent Neural Network for Text Classification with Multi-Task Learning","arxiv_id":"1605.05101","date":"2016-05-17","proceeding":null,"authors":["Pengfei Liu","Xipeng Qiu","Xuanjing Huang"],"abstract":"Neural network based methods have obtained great progress on a variety of\nnatural language processing tasks. However, in most previous works, the models\nare learned based on single-task supervised objectives, which often suffer from\ninsufficient training data. In this paper, we use the multi-task learning\nframework to jointly learn across multiple related tasks. Based on recurrent\nneural network, we propose three different mechanisms of sharing information to\nmodel text with task-specific and shared layers. The entire network is trained\njointly on all these tasks. Experiments on four benchmark text classification\ntasks show that our proposed models can improve the performance of a task with\nthe help of other related tasks.","url_abs":"http://arxiv.org/abs/1605.05101v1","url_pdf":"http://arxiv.org/pdf/1605.05101v1.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":[],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"emotion-recognition-in-conversation","task_name":"Emotion Recognition in Conversation"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"multi-task-learning","task_name":"Multi-Task Learning"},{"task_slug":"text-classification","task_name":"Text Classification"},{"task_slug":"text-classification-1","task_name":"text-classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/emotion-recognition-in-conversation-on-cped","task":"Emotion Recognition in Conversation","dataset":"CPED","model":"TextRNN","rank_in_archive_order":10,"of":11,"metrics":{"Accuracy of Sentiment":"47.89","Macro-F1 of Sentiment":"37.07"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1605.05101","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}