{"id":"https://openalex.org/W4416516271","doi":"https://doi.org/10.48550/arxiv.2506.23527","title":"On Recipe Memorization and Creativity in Large Language Models: Is Your Model a Creative Cook, a Bad Cook, or Merely a Plagiator?","display_name":"On Recipe Memorization and Creativity in Large Language Models: Is Your Model a Creative Cook, a Bad Cook, or Merely a Plagiator?","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416516271","doi":"https://doi.org/10.48550/arxiv.2506.23527"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2506.23527","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.23527","pdf_url":"https://arxiv.org/pdf/2506.23527","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.23527","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120372044","display_name":"Jan Kvapil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kvapil, Jan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5077658504","display_name":"Martin Faj\u010d\u00edk","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fajcik, Martin","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/T11925","display_name":"Culinary Culture and Tourism","score":0.1274999976158142,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11925","display_name":"Culinary Culture and Tourism","score":0.1274999976158142,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.1006999984383583,"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/T12128","display_name":"AI in Service Interactions","score":0.07249999791383743,"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/recipe","display_name":"Recipe","score":0.9049999713897705},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6797999739646912},{"id":"https://openalex.org/keywords/nonsense","display_name":"Nonsense","score":0.5723000168800354},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5568000078201294},{"id":"https://openalex.org/keywords/creativity","display_name":"Creativity","score":0.5504999756813049},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.491100013256073},{"id":"https://openalex.org/keywords/ingredient","display_name":"Ingredient","score":0.4724000096321106},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.4251999855041504},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.421099990606308}],"concepts":[{"id":"https://openalex.org/C2778671685","wikidata":"https://www.wikidata.org/wiki/Q219239","display_name":"Recipe","level":2,"score":0.9049999713897705},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6797999739646912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6470000147819519},{"id":"https://openalex.org/C62923972","wikidata":"https://www.wikidata.org/wiki/Q600499","display_name":"Nonsense","level":3,"score":0.5723000168800354},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5568000078201294},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5562999844551086},{"id":"https://openalex.org/C11012388","wikidata":"https://www.wikidata.org/wiki/Q170658","display_name":"Creativity","level":2,"score":0.5504999756813049},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.542900025844574},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.491100013256073},{"id":"https://openalex.org/C2780589914","wikidata":"https://www.wikidata.org/wiki/Q10675206","display_name":"Ingredient","level":2,"score":0.4724000096321106},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.4251999855041504},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.421099990606308},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3384000062942505},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28119999170303345},{"id":"https://openalex.org/C2778143727","wikidata":"https://www.wikidata.org/wiki/Q1820650","display_name":"Readability","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C2778473407","wikidata":"https://www.wikidata.org/wiki/Q1459574","display_name":"Compendium","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C2780922921","wikidata":"https://www.wikidata.org/wiki/Q255189","display_name":"Paraphrase","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C30038468","wikidata":"https://www.wikidata.org/wiki/Q4354775","display_name":"Memorization","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C2776372474","wikidata":"https://www.wikidata.org/wiki/Q508291","display_name":"Simplicity","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2506.23527","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.23527","pdf_url":"https://arxiv.org/pdf/2506.23527","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.23527","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.23527","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":"pmh:oai:arXiv.org:2506.23527","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.23527","pdf_url":"https://arxiv.org/pdf/2506.23527","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,195],"work-in-progress":[1],"investigates":[2],"the":[3,176,213],"memorization,":[4,24,202],"creativity,":[5,25,203],"and":[6,26,38,81,137,145,162,165,180,204],"nonsense":[7,158,205],"found":[8,118],"in":[9,28,50,119,206],"cooking":[10],"recipes":[11,72],"generated":[12,73,207],"from":[13,101],"Large":[14],"Language":[15],"Models":[16],"(LLMs).":[17],"Precisely,":[18],"we":[19,63,149],"aim":[20,135],"(i)":[21],"to":[22,40,44,52,56,84,92,189],"analyze":[23],"non-sense":[27],"LLMs":[29],"using":[30],"a":[31,47,65],"small,":[32],"high-quality":[33],"set":[34],"of":[35,58,201,212],"human":[36,48,67,174],"judgments":[37],"(ii)":[39,136],"evaluate":[41],"potential":[42],"approaches":[43],"automate":[45],"such":[46],"annotation":[49,68],"order":[51],"scale":[53,138],"our":[54,139],"study":[55],"hundreds":[57],"recipes.":[59],"To":[60,133],"achieve":[61,134],"(i),":[62],"conduct":[64],"detailed":[66],"on":[69,130,192],"20":[70],"preselected":[71],"by":[74],"LLM":[75,147],"(Mixtral),":[76],"extracting":[77],"each":[78],"recipe's":[79],"ingredients":[80,114,161],"step-by-step":[82],"actions":[83],"assess":[85],"which":[86,99],"elements":[87],"are":[88],"memorized--i.e.,":[89],"directly":[90],"traceable":[91],"online":[93,120],"sources":[94],"possibly":[95],"seen":[96,123],"during":[97,124],"training--and":[98],"arise":[100],"genuine":[102],"creative":[103,215],"synthesis":[104],"or":[105],"outright":[106],"nonsense.":[107],"We":[108],"find":[109],"that":[110,115,154],"Mixtral":[111],"consistently":[112],"reuses":[113],"can":[116],"be":[117],"documents,":[121],"potentially":[122],"model":[125],"training,":[126],"suggesting":[127],"strong":[128],"reliance":[129],"memorized":[131],"content.":[132],"analysis":[140],"beyond":[141],"small":[142],"sample":[143],"sizes":[144],"single":[146],"validation,":[148],"design":[150],"an":[151],"``LLM-as-judge''":[152],"pipeline":[153],"automates":[155],"recipe":[156,163],"generation,":[157],"detection,":[159],"parsing":[160],"steps,":[164],"their":[166],"annotation.":[167],"For":[168],"instance,":[169],"comparing":[170],"its":[171],"output":[172],"against":[173],"annotations,":[175],"best":[177],"ingredient":[178,193],"extractor":[179],"annotator":[181],"is":[182],"Llama":[183],"3.1+Gemma":[184],"2":[185],"9B,":[186],"achieving":[187],"up":[188],"78%":[190],"accuracy":[191],"matching.":[194],"automated":[196],"framework":[197],"enables":[198],"large-scale":[199],"quantification":[200],"recipes,":[208],"providing":[209],"rigorous":[210],"evidence":[211],"models'":[214],"capacities.":[216]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
