{"id":"https://openalex.org/W7137142412","doi":"https://doi.org/10.48550/arxiv.2603.12683","title":"Experimental evidence of progressive ChatGPT models self-convergence","display_name":"Experimental evidence of progressive ChatGPT models self-convergence","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7137142412","doi":"https://doi.org/10.48550/arxiv.2603.12683"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.12683","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12683","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.12683","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083041537","display_name":"Konstantinos F. Xylogiannopoulos","orcid":"https://orcid.org/0000-0003-2376-898X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xylogiannopoulos, Konstantinos F.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091900079","display_name":"Petros Xanthopoulos","orcid":"https://orcid.org/0000-0002-6633-5191"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xanthopoulos, Petros","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034281379","display_name":"Panagiotis Karampelas","orcid":"https://orcid.org/0000-0003-1684-7612"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karampelas, Panagiotis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5002143061","display_name":"Georgios A. Bakamitsos","orcid":"https://orcid.org/0009-0004-2363-1937"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bakamitsos, Georgios A.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.5821999907493591,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.5821999907493591,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.1354999989271164,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"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/T10028","display_name":"Topic Modeling","score":0.03669999912381172,"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/phenomenon","display_name":"Phenomenon","score":0.7822999954223633},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5659000277519226},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4307999908924103},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.3961000144481659},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.3781999945640564},{"id":"https://openalex.org/keywords/diversity","display_name":"Diversity (politics)","score":0.3765999972820282},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.3610999882221222}],"concepts":[{"id":"https://openalex.org/C50335755","wikidata":"https://www.wikidata.org/wiki/Q483247","display_name":"Phenomenon","level":2,"score":0.7822999954223633},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5659000277519226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5424000024795532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4512999951839447},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4325999915599823},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4307999908924103},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.39800000190734863},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3961000144481659},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3781999945640564},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.3765999972820282},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3668999969959259},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3416000008583069},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C3020672099","wikidata":"https://www.wikidata.org/wiki/Q857354","display_name":"Longitudinal data","level":2,"score":0.3149999976158142},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31150001287460327},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3061000108718872},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.2678999900817871}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.12683","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12683","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.12683","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12683","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.677863359451294,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"that":[4],"undergo":[5],"recursive":[6],"training":[7,149],"on":[8,40,46],"synthetically":[9],"generated":[10,159],"data":[11,145],"are":[12],"susceptible":[13],"to":[14,73,88,94,110,118,126,137],"model":[15,43,166],"collapse,":[16],"a":[17,41,84,102],"phenomenon":[18,162],"marked":[19],"by":[20,121,157],"the":[21,56,123,138,141,152,170],"generation":[22],"of":[23,59,105,140,143,154,169,173,175],"meaningless":[24],"output.":[25],"Existing":[26],"research":[27],"has":[28,69],"examined":[29],"this":[30,75,80],"issue":[31],"from":[32],"either":[33],"theoretical":[34],"or":[35],"empirical":[36],"perspectives,":[37],"often":[38],"focusing":[39],"single":[42],"trained":[44],"recursively":[45],"its":[47],"own":[48],"outputs.":[49,98],"While":[50],"prior":[51],"studies":[52],"have":[53],"cautioned":[54],"against":[55],"potential":[57],"degradation":[58],"LLM":[60,158],"output":[61,132],"quality":[62],"under":[63],"such":[64],"conditions,":[65],"no":[66],"longitudinal":[67],"investigation":[68],"yet":[70],"been":[71],"conducted":[72],"assess":[74],"effect":[76],"over":[77],"time.":[78],"In":[79],"study,":[81],"we":[82],"employ":[83],"text":[85],"similarity":[86],"metric":[87],"evaluate":[89],"different":[90,179],"ChatGPT":[91,107,180],"models'":[92],"capacity":[93],"generate":[95],"diverse":[96],"textual":[97],"Our":[99],"findings":[100],"indicate":[101],"measurable":[103],"decline":[104],"recent":[106],"releases'":[108],"ability":[109],"produce":[111],"varied":[112],"text,":[113],"even":[114],"when":[115],"explicitly":[116],"prompted":[117],"do":[119],"so,":[120],"setting":[122],"temperature":[124],"parameter":[125],"one.":[127],"The":[128,161],"observed":[129],"reduction":[130],"in":[131],"diversity":[133],"may":[134],"be":[135],"attributed":[136],"influence":[139],"amounts":[142],"synthetic":[144],"incorporated":[146],"within":[147],"their":[148],"datasets":[150],"as":[151,165],"result":[153],"internet":[155],"infiltration":[156],"data.":[160],"is":[163],"defined":[164],"self-convergence":[167],"because":[168],"gradual":[171],"increase":[172],"similarities":[174],"produced":[176],"texts":[177],"among":[178],"versions.":[181]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-17T00:00:00"}
