{"type":"ScholarlyArticle","title":"Generating Multiple Diverse Responses with Multi-Mapping and Posterior Mapping Selection","authors":[{"name":"Chaotao Chen","slug":"chaotao-chen","given":"Chaotao","family":"Chen","affiliation":"Baidu Inc. , China"},{"name":"Jinhua Peng","slug":"jinhua-peng","given":"Jinhua","family":"Peng","affiliation":"Baidu Inc. , China"},{"name":"Fan Wang","slug":"fan-wang","given":"Fan","family":"Wang","affiliation":"Baidu Inc. , China"},{"name":"Jun Xu","slug":"jun-xu","given":"Jun","family":"Xu","affiliation":"Harbin Institute of Technology , China"},{"name":"Hua Wu","slug":"hua-wu","given":"Hua","family":"Wu","affiliation":"Baidu Inc. , China"}],"abstract":"In human conversation an input post is open to multiple potential responses, which is typically regarded as a one-to-many problem. Promising approaches mainly incorporate multiple latent mechanisms to build the one-to-many relationship. However, without accurate selection of the latent mechanism corresponding to the target response during training, these methods suffer from a rough optimization of latent mechanisms. In this paper, we propose a multi-mapping mechanism to better capture the one-to-many relationship, where multiple mapping modules are employed as latent mechanisms to model the semantic mappings from an input post to its diverse responses. For accurate optimization of latent mechanisms, a posterior mapping selection module is designed to select the corresponding mapping module according to the target response for further optimization. We also introduce an auxiliary matching loss to facilitate the optimization of posterior mapping selection. Empirical results demonstrate the superiority of our model in generating multiple diverse and informative responses over the state-of-the-art methods.","doi":"10.24963/ijcai.2019/683","url":"https://ijcai.org/proceedings/2019/683","pdf":"https://ijcai.org/proceedings/2019/0683.pdf","markdown":"https://ijcai.org/proceedings/2019/683.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/683","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Natural Language Processing","track":"Main track","number":683,"pages":{"first":4918,"last":4924},"keywords":["Natural Language Processing: Natural Language Generation","Natural Language Processing: Dialogue"],"videos":[],"references":[{"position":1,"raw":"[Bahdanau et al., 2015] Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 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