{"id":"https://openalex.org/W7138910295","doi":"https://doi.org/10.1109/globecom59602.2025.11432811","title":"On Graph Sparsification with Generative Model and Dual-Reward System for Generalized Tasks","display_name":"On Graph Sparsification with Generative Model and Dual-Reward System for Generalized Tasks","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7138910295","doi":"https://doi.org/10.1109/globecom59602.2025.11432811"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11432811","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130029104","display_name":"Yi-Ying Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I49645291","display_name":"National Taipei University of Education","ror":"https://ror.org/02bzpph30","country_code":"TW","type":"education","lineage":["https://openalex.org/I49645291"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yi-Ying Chen","raw_affiliation_strings":["NTUST,Dept. of CSIE,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTUST,Dept. of CSIE,Taipei,Taiwan","institution_ids":["https://openalex.org/I49645291"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129903028","display_name":"Pin-Yen Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I49645291","display_name":"National Taipei University of Education","ror":"https://ror.org/02bzpph30","country_code":"TW","type":"education","lineage":["https://openalex.org/I49645291"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Pin-Yen Lin","raw_affiliation_strings":["NTUST,Dept. of CSIE,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTUST,Dept. of CSIE,Taipei,Taiwan","institution_ids":["https://openalex.org/I49645291"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129991613","display_name":"Tzu-Hsin Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I49645291","display_name":"National Taipei University of Education","ror":"https://ror.org/02bzpph30","country_code":"TW","type":"education","lineage":["https://openalex.org/I49645291"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tzu-Hsin Lin","raw_affiliation_strings":["NTUST,Dept. of CSIE,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTUST,Dept. of CSIE,Taipei,Taiwan","institution_ids":["https://openalex.org/I49645291"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100738421","display_name":"Yi\u2010Ling Chen","orcid":"https://orcid.org/0000-0002-9191-7169"},"institutions":[{"id":"https://openalex.org/I49645291","display_name":"National Taipei University of Education","ror":"https://ror.org/02bzpph30","country_code":"TW","type":"education","lineage":["https://openalex.org/I49645291"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yi-Ling Chen","raw_affiliation_strings":["NTUST,Dept. of CSIE,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTUST,Dept. of CSIE,Taipei,Taiwan","institution_ids":["https://openalex.org/I49645291"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I49645291"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4301","last_page":"4306"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.8878999948501587,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.8878999948501587,"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/T14347","display_name":"Big Data and Digital Economy","score":0.01860000006854534,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12292","display_name":"Graph Theory and Algorithms","score":0.01720000058412552,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/adaptability","display_name":"Adaptability","score":0.6198999881744385},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5891000032424927},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5576000213623047},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5472999811172485},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5443000197410583},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4120999872684479},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3912999927997589}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7312999963760376},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.6198999881744385},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5891000032424927},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5576000213623047},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5472999811172485},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5443000197410583},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5001000165939331},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4756999909877777},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45239999890327454},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4120999872684479},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3912999927997589},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3781999945640564},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.33880001306533813},{"id":"https://openalex.org/C47458327","wikidata":"https://www.wikidata.org/wiki/Q910404","display_name":"Random graph","level":3,"score":0.3386000096797943},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom59602.2025.11432811","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1981377410","https://openalex.org/W1997092589","https://openalex.org/W1999170091","https://openalex.org/W2153959628","https://openalex.org/W2241870169","https://openalex.org/W2400271895","https://openalex.org/W2620315948","https://openalex.org/W2963239847","https://openalex.org/W3128601901","https://openalex.org/W4290877352","https://openalex.org/W4318812488","https://openalex.org/W4379117687","https://openalex.org/W4400909541"],"related_works":[],"abstract_inverted_index":{"Graph":[0,49],"sparsification":[1,191],"is":[2,151,185],"a":[3,45,186],"vital":[4],"technique":[5],"that":[6,129,158,188,205],"aims":[7],"to":[8,33,68,114,116,137,142,154,195],"reduce":[9],"network":[10],"complexity":[11],"while":[12],"preserving":[13],"essential":[14],"functionality.":[15],"Traditional":[16],"approaches":[17,192],"often":[18],"involve":[19],"edge":[20,126],"selection":[21],"and":[22,54,95,117,134,175,218],"deletion":[23],"based":[24],"on":[25,200],"the":[26,65,71,83,92,97,103,109,125,152,163,171,177,182,221],"given":[27],"task.":[28],"However,":[29],"these":[30],"methods":[31,209],"tend":[32],"lack":[34],"adaptability":[35],"across":[36,210],"diverse":[37],"tasks.":[38,121],"To":[39],"address":[40],"this":[41],"limitation,":[42],"we":[43],"propose":[44],"novel":[46],"framework":[47,63],"called":[48],"Sparsification":[50],"with":[51],"Generative":[52],"Model":[53],"Dual-Reward":[55],"System":[56],"for":[57,119],"Generalized":[58],"Tasks":[59],"(GSGT).":[60],"The":[61,78,197],"GSGT":[62,81,150,206],"employs":[64],"generative":[66],"model":[67,113],"gradually":[69],"comprehend":[70],"entire":[72],"graph\u2019s":[73,178],"structure":[74],"via":[75],"random":[76,110],"walks.":[77],"training":[79],"of":[80,91,149,220],"leverages":[82],"local":[84,89],"reward":[85,99],"obtained":[86,100],"by":[87,101],"evaluating":[88,102],"nodes":[90],"enhanced":[93],"graph,":[94],"also":[96],"global":[98],"synthesis":[104,127],"graph.":[105,165],"These":[106,166],"rewards":[107],"guide":[108],"walk":[111],"generation":[112],"adapt":[115],"optimize":[118],"various":[120,211],"We":[122],"further":[123,213],"utilize":[124],"process":[128],"jointly":[130],"considers":[131],"graph":[132,139],"connectivity":[133],"performance":[135,179],"assessment":[136],"customize":[138],"assembly":[140],"according":[141],"specific":[143],"task":[144],"requirements.":[145],"A":[146],"notable":[147],"feature":[148],"ability":[153],"generate":[155],"artificial":[156,167],"edges":[157,168,174],"do":[159],"not":[160],"exist":[161],"in":[162],"original":[164],"can":[169],"replace":[170],"existing":[172,208],"weak":[173],"enhance":[176],"even":[180],"beyond":[181],"original.":[183],"This":[184],"functionality":[187],"many":[189],"traditional":[190],"find":[193],"challenging":[194],"provide.":[196],"experimental":[198],"results":[199],"three":[201],"real-world":[202],"datasets":[203],"demonstrate":[204],"outperforms":[207],"tasks,":[212],"affirming":[214],"strong":[215],"generalization":[216],"capabilities":[217],"effectiveness":[219],"proposed":[222],"framework.":[223]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-20T00:00:00"}