{"id":"https://openalex.org/W7130693797","doi":"https://doi.org/10.1109/access.2026.3666781","title":"Human or Machine? A Survey on Machine-Generated Text Detection","display_name":"Human or Machine? A Survey on Machine-Generated Text Detection","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7130693797","doi":"https://doi.org/10.1109/access.2026.3666781"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3666781","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3666781","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3666781","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071285429","display_name":"Zainab Ahmad","orcid":null},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Zainab Ahmad","raw_affiliation_strings":["Centro de Investigaci&#x00F3;n en Computaci&#x00F3;n, Instituto Polit&#x00E9;cnico Nacional, UPALM-Zacatenco, Mexico City, Mexico"],"raw_orcid":"https://orcid.org/0009-0006-4596-8973","affiliations":[{"raw_affiliation_string":"Centro de Investigaci&#x00F3;n en Computaci&#x00F3;n, Instituto Polit&#x00E9;cnico Nacional, UPALM-Zacatenco, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126522806","display_name":"Miguel Torres-Ruiz","orcid":null},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Miguel Torres-Ruiz","raw_affiliation_strings":["Centro de Investigaci&#x00F3;n en Computaci&#x00F3;n, Instituto Polit&#x00E9;cnico Nacional, UPALM-Zacatenco, Mexico City, Mexico"],"raw_orcid":"https://orcid.org/0000-0001-8289-6979","affiliations":[{"raw_affiliation_string":"Centro de Investigaci&#x00F3;n en Computaci&#x00F3;n, Instituto Polit&#x00E9;cnico Nacional, UPALM-Zacatenco, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100901967","display_name":"Ahmad Mahmood","orcid":"https://orcid.org/0009-0002-0755-3145"},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Ahmad Mahmood","raw_affiliation_strings":["Centro de Investigaci&#x00F3;n en Computaci&#x00F3;n, Instituto Polit&#x00E9;cnico Nacional, UPALM-Zacatenco, Mexico City, Mexico"],"raw_orcid":"https://orcid.org/0009-0002-0755-3145","affiliations":[{"raw_affiliation_string":"Centro de Investigaci&#x00F3;n en Computaci&#x00F3;n, Instituto Polit&#x00E9;cnico Nacional, UPALM-Zacatenco, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126523170","display_name":"Rolando Quintero","orcid":null},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Rolando Quintero","raw_affiliation_strings":["Centro de Investigaci&#x00F3;n en Computaci&#x00F3;n, Instituto Polit&#x00E9;cnico Nacional, UPALM-Zacatenco, Mexico City, Mexico"],"raw_orcid":"https://orcid.org/0000-0003-4454-8791","affiliations":[{"raw_affiliation_string":"Centro de Investigaci&#x00F3;n en Computaci&#x00F3;n, Instituto Polit&#x00E9;cnico Nacional, UPALM-Zacatenco, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126471976","display_name":"Iqra Ameer","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Iqra Ameer","raw_affiliation_strings":["Division of Science and Engineering, The Pennsylvania State University, Abington, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1134-9713","affiliations":[{"raw_affiliation_string":"Division of Science and Engineering, The Pennsylvania State University, Abington, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021857737","display_name":"Necva B\u00f6l\u00fcc\u00fc","orcid":"https://orcid.org/0000-0001-8121-3048"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Necva B\u00f6l\u00fcc\u00fc","raw_affiliation_strings":["Data61, CSIRO, Sydney, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data61, CSIRO, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I1292875679"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":12.1051,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.96986901,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"14","issue":null,"first_page":"34113","last_page":"34136"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.21459999680519104,"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":0.21459999680519104,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.10220000147819519,"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/T12488","display_name":"Mental Health via Writing","score":0.093299999833107,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/perplexity","display_name":"Perplexity","score":0.9455000162124634},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5906999707221985},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5647000074386597},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.48249998688697815},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.46219998598098755},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.44020000100135803},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.3882000148296356},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.3725999891757965}],"concepts":[{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.9455000162124634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7390999794006348},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.609499990940094},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5906999707221985},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.569599986076355},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5647000074386597},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.48249998688697815},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46810001134872437},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.46219998598098755},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.44020000100135803},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3882000148296356},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.32710000872612},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.32120001316070557},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C2474386","wikidata":"https://www.wikidata.org/wiki/Q461183","display_name":"Text corpus","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C2985684807","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Text generation","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C2992249680","wikidata":"https://www.wikidata.org/wiki/Q315","display_name":"Linguistic diversity","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2565000057220459},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3666781","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3666781","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c3bd6342f34a44dfa113c7577ce14bda","is_oa":true,"landing_page_url":"https://doaj.org/article/c3bd6342f34a44dfa113c7577ce14bda","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 34113-34136 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3666781","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3666781","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.710975706577301}],"awards":[{"id":"https://openalex.org/G8279963043","display_name":null,"funder_award_id":"20251107","funder_id":"https://openalex.org/F4320321694","funder_display_name":"Instituto Polit\u00e9cnico Nacional"}],"funders":[{"id":"https://openalex.org/F4320321694","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W2585345551","https://openalex.org/W2963748441","https://openalex.org/W2963929190","https://openalex.org/W3001434439","https://openalex.org/W3031781733","https://openalex.org/W3045462440","https://openalex.org/W3205136326","https://openalex.org/W3212499710","https://openalex.org/W4200259318","https://openalex.org/W4254182148","https://openalex.org/W4286829109","https://openalex.org/W4300952844","https://openalex.org/W4312910992","https://openalex.org/W4383376720","https://openalex.org/W4384282605","https://openalex.org/W4385237904","https://openalex.org/W4385570226","https://openalex.org/W4389520338","https://openalex.org/W4389977394","https://openalex.org/W4390919465","https://openalex.org/W4391230058","https://openalex.org/W4392736762","https://openalex.org/W4392913295","https://openalex.org/W4392938070","https://openalex.org/W4396667547","https://openalex.org/W4399205244","https://openalex.org/W4400976635","https://openalex.org/W4401041989","https://openalex.org/W4401042507","https://openalex.org/W4401043701","https://openalex.org/W4401983380","https://openalex.org/W4402320017","https://openalex.org/W4402531536","https://openalex.org/W4402667057","https://openalex.org/W4402671223","https://openalex.org/W4402672003","https://openalex.org/W4402997147","https://openalex.org/W4403848310","https://openalex.org/W4405003677","https://openalex.org/W4405114800","https://openalex.org/W4405183026","https://openalex.org/W4406236959","https://openalex.org/W4406916682","https://openalex.org/W4406982988","https://openalex.org/W4406983030","https://openalex.org/W4407128422","https://openalex.org/W4407551092","https://openalex.org/W4408072273","https://openalex.org/W4408480938","https://openalex.org/W4408687188","https://openalex.org/W4409166760","https://openalex.org/W4409166874","https://openalex.org/W4411630239","https://openalex.org/W4412889929","https://openalex.org/W4413169625","https://openalex.org/W4414116672","https://openalex.org/W4416223410"],"related_works":[],"abstract_inverted_index":{"As":[0],"generative":[1],"AI":[2,94],"advances":[3],"rapidly":[4],"across":[5,139],"education,":[6],"research,":[7],"medicine,":[8],"and":[9,19,37,48,67,96,119,137,141,147],"journalism,":[10],"machine-generated":[11],"text":[12,65],"(MGT)":[13],"raises":[14],"questions":[15],"about":[16],"authenticity,":[17],"ethics,":[18],"social":[20],"impact.":[21],"To":[22],"ground":[23],"this":[24],"discussion,":[25],"we":[26],"conducted":[27],"a":[28],"linguistic":[29],"analysis,":[30],"covering":[31],"phonology,":[32],"morphology,":[33],"syntax,":[34],"semantics,":[35],"lexicon,":[36],"pragmatics,":[38],"which":[39],"uncovers":[40],"robust":[41,151],"MGT":[42,130],"signatures,":[43],"such":[44],"as":[45],"lower":[46],"perplexity":[47],"simpler":[49],"morphology.":[50],"We":[51],"then":[52],"consolidate":[53],"the":[54,120],"state-of-the-art":[55],"by":[56,143],"reviewing":[57],"30":[58],"benchmark":[59],"corpora,":[60],"totaling":[61],"over":[62],"4":[63],"million":[64],"samples,":[66],"44":[68],"empirical":[69],"studies,":[70],"including":[71],"outcomes":[72],"from":[73],"six":[74],"major":[75],"shared":[76],"tasks.":[77],"Detection":[78],"approaches":[79],"are":[80],"grouped":[81],"into":[82],"five":[83],"broad":[84],"classes:":[85],"classical":[86],"machine":[87],"learning,":[88,90],"deep":[89],"transformer-based":[91],"architectures,":[92],"commercial":[93],"detectors,":[95],"statistical":[97],"tools.":[98],"Transformer":[99],"models":[100],"achieve":[101],"near-perfect":[102],"accuracy":[103],"(\u2248100%),":[104],"while":[105],"human":[106],"evaluators":[107],"peak":[108],"at":[109],"\u224877%":[110],"accuracy.":[111],"This":[112],"survey":[113],"also":[114],"highlights":[115],"common":[116],"evaluation":[117],"setups":[118],"core":[121],"performance":[122],"measures":[123],"used":[124],"to":[125],"assess":[126],"model":[127],"effectiveness.":[128],"Future":[129],"detectors":[131],"can":[132],"become":[133],"truly":[134],"fair,":[135],"scalable,":[136],"effective":[138],"languages":[140],"domains":[142],"expanding":[144],"corpus":[145],"diversity":[146],"innovating":[148],"resource-efficient,":[149],"adversarially":[150],"methods.":[152]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-09T07:00:12.390032","created_date":"2026-02-21T00:00:00"}
