{"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/jointly-optimizing-diversity-and-relevance-in","title":"Jointly Optimizing Diversity and Relevance in Neural Response Generation","arxiv_id":"1902.11205","date":"2019-02-28","proceeding":"NAACL 2019 6","authors":["Xiang Gao","Sungjin Lee","Yizhe Zhang","Chris Brockett","Michel Galley","Jianfeng Gao","Bill Dolan"],"abstract":"Although recent neural conversation models have shown great potential, they\noften generate bland and generic responses. While various approaches have been\nexplored to diversify the output of the conversation model, the improvement\noften comes at the cost of decreased relevance. In this paper, we propose a\nSpaceFusion model to jointly optimize diversity and relevance that essentially\nfuses the latent space of a sequence-to-sequence model and that of an\nautoencoder model by leveraging novel regularization terms. As a result, our\napproach induces a latent space in which the distance and direction from the\npredicted response vector roughly match the relevance and diversity,\nrespectively. This property also lends itself well to an intuitive\nvisualization of the latent space. Both automatic and human evaluation results\ndemonstrate that the proposed approach brings significant improvement compared\nto strong baselines in both diversity and relevance.","url_abs":"http://arxiv.org/abs/1902.11205v3","url_pdf":"http://arxiv.org/pdf/1902.11205v3.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":"chatbot","task_name":"Chatbot"},{"task_slug":"dialogue-generation","task_name":"Dialogue Generation"},{"task_slug":"diversity","task_name":"Diversity"},{"task_slug":"response-generation","task_name":"Response Generation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/dialogue-generation-on-reddit-multi-ref","task":"Dialogue Generation","dataset":"Reddit (multi-ref)","model":"SpaceFusion","rank_in_archive_order":1,"of":1,"metrics":{"interest (human)":"2.53","relevance (human)":"2.72"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1902.11205","atlas_url":"https://app.syntology.ai/?focus=1902.11205","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}