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Existing works have achieved excellent results by employing multi-granularity of dialogue history information, indicating the effectiveness of multi-level historical information. However, these works often focus on exploring the hierarchical information of dialogue history, while neglecting the multi-granularity utilization in response, important information that holds an impact on the decoding process. Therefore, this paper proposes a model for document information selection based on multi-granularity responses. By integrating the document selection results at the response word level and semantic unit level, the model enhances its capability in knowledge selection and produces better responses. For the division at the semantic unit level of the response, we propose two semantic unit division methods, static and dynamic. Experiments on two public datasets show that our models combining static or dynamic semantic unit levels significantly outperform baseline models.<\/jats:p>","DOI":"10.1007\/s11063-024-11633-w","type":"journal-article","created":{"date-parts":[[2024,5,28]],"date-time":"2024-05-28T22:02:29Z","timestamp":1716933749000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhancing Document Information Selection Through Multi-Granularity Responses for Dialogue Generation"],"prefix":"10.1007","volume":"56","author":[{"given":"Meiqi","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kangyu","family":"Qiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuyue","family":"Xing","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Caixia","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojie","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,5,28]]},"reference":[{"key":"11633_CR1","unstructured":"Ma L, Zhang W, Li M, Liu T (2020) A survey of document grounded dialogue systems (DGDS). 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