{"id":"https://openalex.org/W4416799899","doi":"https://doi.org/10.1109/snpd65828.2025.11254671","title":"Application and Optimization of Large Models Based on Prompt Tuning for Fact-Check-Worthiness Estimation","display_name":"Application and Optimization of Large Models Based on Prompt Tuning for Fact-Check-Worthiness Estimation","publication_year":2025,"publication_date":"2025-06-25","ids":{"openalex":"https://openalex.org/W4416799899","doi":"https://doi.org/10.1109/snpd65828.2025.11254671"},"language":null,"primary_location":{"id":"doi:10.1109/snpd65828.2025.11254671","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd65828.2025.11254671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/ACIS 29th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","raw_type":"proceedings-article"},"type":"article","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/A5034121895","display_name":"Yeonseop Yu","orcid":"https://orcid.org/0000-0001-5355-278X"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yinglong Yu","raw_affiliation_strings":["Communication University of China,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Communication University of China,Beijing,China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052847653","display_name":"Hao Shen","orcid":"https://orcid.org/0000-0001-6481-4941"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Shen","raw_affiliation_strings":["Communication University of China,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Communication University of China,Beijing,China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhengyi Lyu","orcid":null},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyi Lyu","raw_affiliation_strings":["Communication University of China,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Communication University of China,Beijing,China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101162822","display_name":"Qi He","orcid":null},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi He","raw_affiliation_strings":["Communication University of China,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Communication University of China,Beijing,China","institution_ids":["https://openalex.org/I75689368"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5034121895"],"corresponding_institution_ids":["https://openalex.org/I75689368"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45450672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"193","last_page":"198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.708299994468689,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.708299994468689,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.04019999876618385,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.032499998807907104,"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/leverage","display_name":"Leverage (statistics)","score":0.7544000148773193},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5615000128746033},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5196999907493591},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5019999742507935},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5008000135421753},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4952000081539154},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.3465999960899353}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7544000148773193},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7480999827384949},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5943999886512756},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5615000128746033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5214999914169312},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5196999907493591},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5019999742507935},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5008000135421753},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4952000081539154},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3702999949455261},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C2983703474","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Probability estimation","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C2776990098","wikidata":"https://www.wikidata.org/wiki/Q13579947","display_name":"Misinformation","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.29100000858306885},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.28380000591278076},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.26510000228881836},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2639000117778778}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/snpd65828.2025.11254671","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd65828.2025.11254671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/ACIS 29th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2962739339","https://openalex.org/W2970200208","https://openalex.org/W3021955997","https://openalex.org/W3175475697","https://openalex.org/W3176546569","https://openalex.org/W3185341429","https://openalex.org/W4288079542","https://openalex.org/W4297347595","https://openalex.org/W4391876619"],"related_works":[],"abstract_inverted_index":{"In":[0],"response":[1],"to":[2,47,60],"the":[3,9,36,62,87,97,125,153],"growing":[4],"problem":[5],"of":[6,11,64,100,155],"misinformation":[7],"in":[8,96,130,136,152],"context":[10],"globalization":[12],"and":[13,55,120,143,150],"informatization,":[14],"this":[15,131],"paper":[16],"proposes":[17],"a":[18,30],"classification":[19,98],"method":[20,89,128],"for":[21,32],"fact-check-worthiness":[22,33,101,156],"estimation":[23,34,102],"based":[24],"on":[25,81],"prompt":[26,40,45,57,126],"tuning.":[27,41],"We":[28],"construct":[29],"model":[31],"at":[35],"methodological":[37],"level":[38],"using":[39],"By":[42],"applying":[43],"designed":[44],"templates":[46],"large":[48,116],"language":[49],"models,":[50],"we":[51,84],"establish":[52],"in-context":[53],"learning":[54],"leverage":[56],"tuning":[58],"technology":[59],"improve":[61],"accuracy":[63],"determining":[65],"whether":[66],"claims":[67],"have":[68],"fact-check-worthiness,":[69],"particularly":[70],"when":[71],"dealing":[72],"with":[73],"limited":[74],"or":[75,91],"unlabeled":[76],"data.":[77],"Through":[78],"extensive":[79],"experiments":[80],"public":[82],"datasets,":[83],"demonstrate":[85],"that":[86,124],"proposed":[88,129],"surpasses":[90],"matches":[92],"multiple":[93],"baseline":[94],"methods":[95],"task":[99,154],"assessment,":[103],"including":[104],"classical":[105],"pre-trained":[106],"models":[107,117],"such":[108,139],"as":[109,111,113,140],"BERT,":[110],"well":[112],"recent":[114],"popular":[115],"like":[118],"GPT-3.5":[119],"GPT-4.":[121],"Experiments":[122],"show":[123],"tuning-based":[127],"study":[132],"exhibits":[133],"certain":[134],"advantages":[135],"evaluation":[137],"metrics":[138],"F1":[141],"score":[142],"accuracy,":[144],"thereby":[145],"effectively":[146],"validating":[147],"its":[148],"effectiveness":[149],"advancement":[151],"estimation.":[157]},"counts_by_year":[],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-11-28T00:00:00"}
