{"id":"https://openalex.org/W7152633666","doi":"https://doi.org/10.48550/arxiv.2604.07189","title":"Agent-Driven Corpus Linguistics: A Framework for Autonomous Linguistic Discovery","display_name":"Agent-Driven Corpus Linguistics: A Framework for Autonomous Linguistic Discovery","publication_year":2026,"publication_date":"2026-04-08","ids":{"openalex":"https://openalex.org/W7152633666","doi":"https://doi.org/10.48550/arxiv.2604.07189"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.07189","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07189","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2604.07189","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133239552","display_name":"Jia Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Jia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133291097","display_name":"Weiwei Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Weiwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Xiao, Pengfei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Pengfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133303644","display_name":"Fukun Xing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing, Fukun","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/T12090","display_name":"Language and cultural evolution","score":0.6104000210762024,"subfield":{"id":"https://openalex.org/subfields/3316","display_name":"Cultural Studies"},"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/T12090","display_name":"Language and cultural evolution","score":0.6104000210762024,"subfield":{"id":"https://openalex.org/subfields/3316","display_name":"Cultural Studies"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.08129999786615372,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.032099999487400055,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/corpus-linguistics","display_name":"Corpus linguistics","score":0.6079000234603882},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5734000205993652},{"id":"https://openalex.org/keywords/computational-linguistics","display_name":"Computational linguistics","score":0.4973999857902527},{"id":"https://openalex.org/keywords/falsifiability","display_name":"Falsifiability","score":0.48249998688697815},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4359999895095825},{"id":"https://openalex.org/keywords/text-corpus","display_name":"Text corpus","score":0.40459999442100525},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.38960000872612}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7246999740600586},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6741999983787537},{"id":"https://openalex.org/C532629269","wikidata":"https://www.wikidata.org/wiki/Q865083","display_name":"Corpus linguistics","level":2,"score":0.6079000234603882},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6061999797821045},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5734000205993652},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.4973999857902527},{"id":"https://openalex.org/C116222747","wikidata":"https://www.wikidata.org/wiki/Q220888","display_name":"Falsifiability","level":2,"score":0.48249998688697815},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.43869999051094055},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4359999895095825},{"id":"https://openalex.org/C2474386","wikidata":"https://www.wikidata.org/wiki/Q461183","display_name":"Text corpus","level":2,"score":0.40459999442100525},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3483000099658966},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.28459998965263367},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C172205122","wikidata":"https://www.wikidata.org/wiki/Q777864","display_name":"Linguistic description","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.07189","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07189","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.07189","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07189","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.8437467813491821,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Corpus":[0,29],"linguistics":[1],"has":[2],"traditionally":[3],"relied":[4],"on":[5,204],"human":[6,70],"researchers":[7],"to":[8,41,129],"formulate":[9],"hypotheses,":[10,57],"construct":[11],"queries,":[12],"and":[13,23,63,74,118,170,183,214],"interpret":[14],"results":[15],"-":[16,211,218],"a":[17,35,42,47,95,103,130,151,240],"process":[18],"demanding":[19],"specialized":[20],"technical":[21,237],"skills":[22],"considerable":[24],"time.":[25],"We":[26,90,120],"propose":[27],"Agent-Driven":[28],"Linguistics,":[30],"an":[31,126],"approach":[32],"in":[33,86],"which":[34],"large":[36],"language":[37],"model":[38,187],"(LLM),":[39],"connected":[40],"corpus":[43,88,133,179,207,224],"query":[44],"engine":[45],"via":[46,137],"structured":[48],"tool-use":[49],"interface,":[50],"takes":[51],"over":[52],"the":[53,59,98,110,113,122,138,148,186,198,205,236],"investigative":[54],"cycle:":[55],"generating":[56],"querying":[58],"corpus,":[60],"interpreting":[61],"results,":[62],"refining":[64],"analysis":[65],"across":[66],"multiple":[67],"rounds.":[68],"The":[69],"researcher":[71],"sets":[72],"direction":[73],"evaluates":[75],"final":[76],"output.":[77],"Unlike":[78],"unconstrained":[79],"LLM":[80,127],"generation,":[81],"every":[82],"finding":[83],"is":[84],"anchored":[85],"verifiable":[87],"evidence.":[89],"treat":[91],"this":[92],"not":[93,112],"as":[94,102],"replacement":[96],"for":[97,239],"corpus-based/corpus-driven":[99],"distinction":[100],"but":[101],"complementary":[104],"dimension:":[105],"it":[106],"concerns":[107],"who":[108],"conducts":[109],"inquiry,":[111],"epistemological":[114],"relationship":[115],"between":[116],"theory":[117],"data.":[119],"demonstrate":[121],"framework":[123],"by":[124],"linking":[125],"agent":[128,149,199],"CQP-indexed":[131],"Gutenberg":[132],"(5":[134],"million":[135,209],"tokens)":[136,210],"Model":[139],"Context":[140],"Protocol":[141],"(MCP).":[142],"Given":[143],"only":[144],"\"investigate":[145],"English":[146],"intensifiers,\"":[147],"identified":[150],"diachronic":[152],"relay":[153],"chain":[154],"(so+ADJ":[155],">":[156,158],"very":[157],"really),":[159],"three":[160],"pathways":[161],"of":[162,243],"semantic":[163],"change":[164],"(delexicalization,":[165],"polarity":[166],"fixation,":[167],"metaphorical":[168],"constraint),":[169],"register-sensitive":[171],"distributions.":[172],"A":[173],"controlled":[174],"baseline":[175],"experiment":[176],"shows":[177],"that":[178,185],"grounding":[180],"contributes":[181],"quantification":[182],"falsifiability":[184],"cannot":[188],"produce":[189,228],"from":[190],"training":[191],"data":[192],"alone.":[193],"To":[194],"test":[195],"external":[196],"validity,":[197],"replicated":[200],"two":[201],"published":[202],"studies":[203],"CLMET":[206],"(40":[208],"Claridge":[212],"(2025)":[213],"De":[215],"Smet":[216],"(2013)":[217],"with":[219],"close":[220],"quantitative":[221],"agreement.":[222],"Agent-driven":[223],"research":[225],"can":[226],"thus":[227],"empirically":[229],"grounded":[230],"findings":[231],"at":[232],"machine":[233],"speed,":[234],"lowering":[235],"barrier":[238],"broader":[241],"range":[242],"researchers.":[244]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-10T00:00:00"}