{"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/lstm-based-conversation-models","title":"LSTM based Conversation Models","arxiv_id":"1603.09457","date":"2016-03-31","proceeding":null,"authors":["Yi Luan","Yangfeng Ji","Mari Ostendorf"],"abstract":"In this paper, we present a conversational model that incorporates both\ncontext and participant role for two-party conversations. Different\narchitectures are explored for integrating participant role and context\ninformation into a Long Short-term Memory (LSTM) language model. The\nconversational model can function as a language model or a language generation\nmodel. Experiments on the Ubuntu Dialog Corpus show that our model can capture\nmultiple turn interaction between participants. The proposed method outperforms\na traditional LSTM model as measured by language model perplexity and response\nranking. Generated responses show characteristic differences between the two\nparticipant roles.","url_abs":"http://arxiv.org/abs/1603.09457v1","url_pdf":"http://arxiv.org/pdf/1603.09457v1.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":"lstm-based-conversation-models","repo_url":"https://github.com/michaelfarrell76/End-To-End-Generative-Dialogue","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"torch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"text-generation","task_name":"Text Generation"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1603.09457","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}