{"id":"https://openalex.org/W4410756822","doi":"https://doi.org/10.32604/cmc.2025.063209","title":"GSPT-CVAE: A New Controlled Long Text Generation Method Based on T-CVAE","display_name":"GSPT-CVAE: A New Controlled Long Text Generation Method Based on T-CVAE","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410756822","doi":"https://doi.org/10.32604/cmc.2025.063209"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.063209","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063209","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.063209","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100300092","display_name":"Tian Zhao","orcid":"https://orcid.org/0000-0001-6702-2114"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tian Zhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069393408","display_name":"Jun Tu","orcid":"https://orcid.org/0000-0001-9641-2162"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Tu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Puzheng Quan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Puzheng Quan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Ruisheng Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruisheng Xiong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100300092"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05183637,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"84","issue":"1","first_page":"1351","last_page":"1377"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9502000212669373,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9502000212669373,"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/statistics","display_name":"Statistics","score":0.3973968029022217},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38142406940460205},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.35283392667770386},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2944265305995941}],"concepts":[{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3973968029022217},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38142406940460205},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.35283392667770386},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2944265305995941}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.063209","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063209","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.063209","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.063209","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2953700661","https://openalex.org/W3014521650","https://openalex.org/W3025611493","https://openalex.org/W3046169638","https://openalex.org/W4280574137","https://openalex.org/W4285241415","https://openalex.org/W4385571101","https://openalex.org/W4385572233","https://openalex.org/W4385573827","https://openalex.org/W4385574175","https://openalex.org/W4385734260","https://openalex.org/W4402671633","https://openalex.org/W4404782755"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Aiming":[0],"at":[1,68],"the":[2,22,64,69,81,94,102,119,130,142,165,179,191,197,204,211,218,228,239,244],"problems":[3],"of":[4,7,12,18,24,57,63,80,96,107,122,134,169,186],"incomplete":[5],"characterization":[6],"text":[8,27,100,135,170],"relations,":[9],"poor":[10],"guidance":[11],"potential":[13,91,97,111,123],"representations,":[14],"and":[15,41,67,110,132,149,153,167,172,203,235,238],"low":[16],"quality":[17],"model":[19,35,51,103,143,159,188,213,226,246],"generation":[20,171],"in":[21,164],"field":[23],"controllable":[25],"long":[26,175],"generation,":[28,101],"this":[29,187,222,225],"paper":[30,223],"proposes":[31],"a":[32,53,73,105,214,248],"new":[33],"GSPT-CVAE":[34,212,245],"(Graph":[36],"Structured":[37],"Processing,":[38],"Single":[39],"Vector,":[40],"Potential":[42],"Attention":[43],"Computing":[44],"Transformer-Based":[45],"Conditioned":[46],"Variational":[47],"Autoencoder":[48],"model).":[49],"The":[50,137,158,182],"obtains":[52,72],"more":[54],"comprehensive":[55],"representation":[56,76,98,124,146],"textual":[58,155],"relations":[59],"by":[60,77],"graph-structured":[61,85],"processing":[62,86],"input":[65],"text,":[66,127],"same":[70],"time":[71],"single":[74],"vector":[75,82],"weighted":[78],"merging":[79],"sequences":[83],"after":[84],"to":[87,114,118,128],"get":[88],"an":[89],"effective":[90],"representation.":[92],"In":[93],"process":[95],"guiding":[99,120],"adopts":[104],"combination":[106],"traditional":[108],"embedding":[109],"attention":[112],"calculation":[113],"give":[115],"full":[116],"play":[117],"role":[121],"for":[125],"generating":[126],"improve":[129],"controllability":[131,168],"effectiveness":[133,166],"generation.":[136],"experimental":[138,240],"results":[139,163,241],"show":[140,242],"that":[141,177,243],"has":[144,247],"excellent":[145],"learning":[147],"ability":[148],"can":[150,173],"learn":[151],"rich":[152],"useful":[154],"relationship":[156],"representations.":[157],"also":[160],"achieves":[161],"satisfactory":[162],"generate":[174],"texts":[176],"match":[178],"given":[180],"constraints.":[181],"ROUGE-1":[183],"F1":[184,193,199],"score":[185,194,200,206],"is":[189,195,201,207],"0.243,":[190],"ROUGE-2":[192],"0.041,":[196],"ROUGE-L":[198],"0.22,":[202],"PPL-Word":[205],"34.303,":[208],"which":[209],"gives":[210],"certain":[215,249],"advantage":[216],"over":[217],"baseline":[219],"model.":[220],"Meanwhile,":[221],"compares":[224],"with":[227],"state-of-the-art":[229],"generative":[230],"models":[231],"T5,":[232],"GPT-4,":[233],"Llama2,":[234],"so":[236],"on,":[237],"competitiveness.":[250]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}