{"id":"https://openalex.org/W4399068591","doi":"https://doi.org/10.1007/s11063-024-11633-w","title":"Enhancing Document Information Selection Through Multi-Granularity Responses for Dialogue Generation","display_name":"Enhancing Document Information Selection Through Multi-Granularity Responses for Dialogue Generation","publication_year":2024,"publication_date":"2024-05-28","ids":{"openalex":"https://openalex.org/W4399068591","doi":"https://doi.org/10.1007/s11063-024-11633-w"},"language":"en","primary_location":{"id":"doi:10.1007/s11063-024-11633-w","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s11063-024-11633-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11633-w.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11633-w.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060945106","display_name":"Meiqi Wang","orcid":"https://orcid.org/0000-0001-6724-5537"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Meiqi Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109725059","display_name":"Kangyu Qiao","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kangyu Qiao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102677650","display_name":"Shuyue Xing","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyue Xing","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086592352","display_name":"Caixia Yuan","orcid":"https://orcid.org/0000-0002-3681-4423"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caixia Yuan","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100351306","display_name":"Xiaojie Wang","orcid":"https://orcid.org/0000-0003-2565-5831"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojie Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5060945106"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05331048,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"56","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.8740073442459106},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.7146928310394287},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6793656349182129},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5528883934020996},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2650611400604248},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07923409342765808}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.8740073442459106},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7146928310394287},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6793656349182129},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5528883934020996},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2650611400604248},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07923409342765808}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11063-024-11633-w","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s11063-024-11633-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11633-w.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11063-024-11633-w","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s11063-024-11633-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11633-w.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399068591.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1902237438","https://openalex.org/W2418993857","https://openalex.org/W2561368124","https://openalex.org/W2734443755","https://openalex.org/W2891103209","https://openalex.org/W2891826200","https://openalex.org/W2908331278","https://openalex.org/W2951508633","https://openalex.org/W2951563833","https://openalex.org/W2962883855","https://openalex.org/W2962896208","https://openalex.org/W2963945575","https://openalex.org/W2964302946","https://openalex.org/W2964458951","https://openalex.org/W2997300509","https://openalex.org/W2997896082","https://openalex.org/W2998083599","https://openalex.org/W3022187094","https://openalex.org/W3034999214","https://openalex.org/W3093680609","https://openalex.org/W3100949457","https://openalex.org/W3104777900","https://openalex.org/W3160293015","https://openalex.org/W3163646812","https://openalex.org/W3171600947","https://openalex.org/W3198455100","https://openalex.org/W3199691415","https://openalex.org/W3202390784","https://openalex.org/W4285301431","https://openalex.org/W4312163908","https://openalex.org/W4321854279","https://openalex.org/W4385572533"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W2999756192","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W4382701072"],"abstract_inverted_index":{"Abstract":[0],"Document":[1],"information":[2,15,53,65,82],"selection":[3,16,83,92,110],"is":[4],"an":[5,68],"essential":[6],"part":[7],"of":[8,33,40,54,123],"document-grounded":[9],"dialogue":[10,22,34,55],"tasks,":[11],"and":[12,99,111,134],"more":[13,20],"accurate":[14],"results":[17,29,93],"can":[18],"provide":[19],"appropriate":[21],"responses.":[23,87,114],"Existing":[24],"works":[25,46],"have":[26],"achieved":[27],"excellent":[28],"by":[30],"employing":[31],"multi-granularity":[32,60,86],"history":[35],"information,":[36],"indicating":[37],"the":[38,51,59,71,90,95,103,116,119,124],"effectiveness":[39],"multi-level":[41],"historical":[42],"information.":[43],"However,":[44],"these":[45],"often":[47],"focus":[48],"on":[49,70,85,137],"exploring":[50],"hierarchical":[52],"history,":[56],"while":[57],"neglecting":[58],"utilization":[61],"in":[62,108],"response,":[63,125],"important":[64],"that":[66,142],"holds":[67],"impact":[69],"decoding":[72],"process.":[73],"Therefore,":[74],"this":[75],"paper":[76],"proposes":[77],"a":[78],"model":[79,104],"for":[80],"document":[81,91],"based":[84],"By":[88],"integrating":[89],"at":[94,118],"response":[96],"word":[97],"level":[98,122],"semantic":[100,120,129,149],"unit":[101,121,130,150],"level,":[102],"enhances":[105],"its":[106],"capability":[107],"knowledge":[109],"produces":[112],"better":[113],"For":[115],"division":[117,131],"we":[126],"propose":[127],"two":[128,138],"methods,":[132],"static":[133,146],"dynamic.":[135],"Experiments":[136],"public":[139],"datasets":[140],"show":[141],"our":[143],"models":[144],"combining":[145],"or":[147],"dynamic":[148],"levels":[151],"significantly":[152],"outperform":[153],"baseline":[154],"models.":[155]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
