{"id":"https://openalex.org/W7162419901","doi":"https://doi.org/10.48550/arxiv.2605.24850","title":"Repeated Sequences Reveal Gaps between Large Language Models and Natural Language","display_name":"Repeated Sequences Reveal Gaps between Large Language Models and Natural Language","publication_year":2026,"publication_date":"2026-05-24","ids":{"openalex":"https://openalex.org/W7162419901","doi":"https://doi.org/10.48550/arxiv.2605.24850"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.24850","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24850","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.2605.24850","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073822077","display_name":"Kumiko Tanaka\u2010Ishii","orcid":"https://orcid.org/0000-0003-1752-3951"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tanaka-Ishii, Kumiko","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5073822077"],"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/T10028","display_name":"Topic Modeling","score":0.18700000643730164,"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":0.18700000643730164,"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/T13629","display_name":"Text Readability and Simplification","score":0.1152999997138977,"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":0.0917000025510788,"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/natural-language","display_name":"Natural language","score":0.5562000274658203},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.53329998254776},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.42329999804496765},{"id":"https://openalex.org/keywords/fluency","display_name":"Fluency","score":0.3889000117778778},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.382999986410141},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.36230000853538513},{"id":"https://openalex.org/keywords/language-identification","display_name":"Language identification","score":0.3077000081539154},{"id":"https://openalex.org/keywords/natural-language-understanding","display_name":"Natural language understanding","score":0.30630001425743103}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6463000178337097},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5968999862670898},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5702999830245972},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.5562000274658203},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.53329998254776},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.42329999804496765},{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.3889000117778778},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.382999986410141},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C129792486","wikidata":"https://www.wikidata.org/wiki/Q1050419","display_name":"Language identification","level":3,"score":0.3077000081539154},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.30630001425743103},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.30090001225471497},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.26510000228881836},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.26420000195503235},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.24850","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24850","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.2605.24850","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24850","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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7744898796081543}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Evaluating":[0],"whether":[1],"large":[2],"language":[3,11,111,164],"models":[4,87],"(LLMs)":[5],"capture":[6],"the":[7,34,95],"structure":[8,71],"of":[9,38,92],"natural":[10,110,163],"beyond":[12,169],"local":[13],"fluency":[14],"remains":[15],"an":[16],"open":[17],"challenge.":[18],"Existing":[19],"evaluation":[20,45],"methods,":[21],"largely":[22],"based":[23,47],"on":[24,48,76],"task":[25],"performance":[26],"or":[27,102],"short-context":[28],"behavior,":[29],"provide":[30],"limited":[31],"insight":[32],"into":[33],"long-range":[35,160],"statistical":[36],"organization":[37],"generated":[39],"text.":[40],"We":[41],"propose":[42],"a":[43,151],"complementary":[44],"framework":[46],"repeated":[49],"subsequences.":[50],"By":[51],"analyzing":[52],"their":[53],"distribution":[54],"across":[55,125],"scales":[56],"and":[57,79,134],"relating":[58],"it":[59],"to":[60],"higher-order":[61],"R\u00e9nyi":[62],"entropies,":[63],"we":[64],"probe":[65],"how":[66],"texts":[67,78,82,131],"reuse":[68],"previously":[69],"established":[70],"under":[72],"finite-length":[73],"conditions.":[74],"Experiments":[75],"human-written":[77],"length-matched":[80],"GPT-generated":[81,130],"show":[83,132],"that,":[84],"while":[85],"power-law":[86],"can":[88],"describe":[89],"restricted":[90],"ranges":[91],"block":[93],"length,":[94],"observed":[96],"entropy":[97,149],"growth":[98],"is":[99],"often":[100],"equally":[101],"better":[103],"characterized":[104],"by":[105],"logarithmic--power":[106],"forms.":[107],"Across":[108],"datasets,":[109],"exhibits":[112],"stable":[113],"entropy-growth":[114],"patterns":[115],"over":[116],"accessible":[117],"ranges,":[118],"with":[119,141],"consistent":[120],"average":[121],"behavior":[122],"despite":[123],"variability":[124],"individual":[126],"texts.":[127],"In":[128],"contrast,":[129],"systematic":[133,157],"statistically":[135],"significant":[136],"shifts":[137],"in":[138,159],"estimated":[139],"exponents":[140],"model":[142],"size.":[143],"These":[144],"results":[145],"demonstrate":[146],"that":[147,155],"repeated-subsequence":[148],"provides":[150],"quantitative":[152],"structural":[153],"diagnostic":[154],"reveals":[156],"differences":[158],"organization,":[161],"distinguishing":[162],"from":[165],"state-of-the-art":[166],"LLM":[167],"outputs":[168],"surface-level":[170],"fluency.":[171]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-27T00:00:00"}
