{"id":"https://openalex.org/W7128498655","doi":"https://doi.org/10.48550/arxiv.2602.07298","title":"Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation","display_name":"Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation","publication_year":2026,"publication_date":"2026-02-07","ids":{"openalex":"https://openalex.org/W7128498655","doi":"https://doi.org/10.48550/arxiv.2602.07298"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.07298","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053072892","display_name":"Benyu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Benyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125498076","display_name":"Qiang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Qiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125553237","display_name":"Jianpeng Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Jianpeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125517035","display_name":"Hong-You Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Hong-You","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123715831","display_name":"Qifei Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Qifei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125477742","display_name":"Wei Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103197641","display_name":"Shen Li","orcid":"https://orcid.org/0009-0007-2093-8230"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Shen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125505997","display_name":"Jia Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125587710","display_name":"Jiahao Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jiahao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001542440","display_name":"Xiangjun Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Xiangjun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125477820","display_name":"Hong Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Hong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5053072892"],"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/T10203","display_name":"Recommender Systems and Techniques","score":0.5712000131607056,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.5712000131607056,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.05130000039935112,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.03999999910593033,"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/synthetic-data","display_name":"Synthetic data","score":0.6883000135421753},{"id":"https://openalex.org/keywords/perplexity","display_name":"Perplexity","score":0.6316999793052673},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.54339998960495},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4438000023365021},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4253000020980835},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.38850000500679016},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.34850001335144043}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7480999827384949},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.6883000135421753},{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.6316999793052673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5497999787330627},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.54339998960495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48489999771118164},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4643000066280365},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4253000020980835},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.38850000500679016},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.34850001335144043},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32030001282691956},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2623000144958496}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.07298","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.07298","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.07298","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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.07298","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"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],"represent":[4],"a":[5,62,77,173],"promising":[6],"frontier":[7],"for":[8,27,66,81,89,112,126,138,145,176],"recommender":[9],"systems,":[10],"yet":[11],"their":[12],"development":[13],"has":[14],"been":[15],"impeded":[16],"by":[17,75,95],"the":[18,42,82,90,139,182,187],"absence":[19],"of":[20,48,92],"predictable":[21,162],"scaling":[22,144,178],"laws,":[23],"which":[24],"are":[25],"crucial":[26],"guiding":[28],"research":[29,188],"and":[30,46,161],"optimizing":[31],"resource":[32],"allocation.":[33],"We":[34,84],"hypothesize":[35],"that":[36,71,97,148],"this":[37],"may":[38],"be":[39],"attributed":[40],"to":[41,194],"inherent":[43],"noise,":[44],"bias,":[45],"incompleteness":[47],"raw":[49],"user":[50,129],"interaction":[51],"data":[52,70,106,118,168,192],"in":[53,119,181],"prior":[54],"continual":[55],"pre-training":[56],"(CPT)":[57],"efforts.":[58],"This":[59],"paper":[60],"introduces":[61],"novel,":[63],"layered":[64],"framework":[65],"generating":[67],"high-quality":[68],"synthetic":[69,105,167],"circumvents":[72],"such":[73],"issues":[74],"creating":[76],"curated,":[78],"pedagogical":[79],"curriculum":[80,94],"LLM.":[83],"provide":[85],"powerful,":[86],"direct":[87],"evidence":[88],"utility":[91],"our":[93,103,153],"showing":[96],"standard":[98],"sequential":[99],"models":[100,114],"trained":[101,115],"on":[102,110,116,133,152],"principled":[104],"significantly":[107],"outperform":[108],"($+130\\%$":[109],"recall@100":[111],"SasRec)":[113],"real":[117],"downstream":[120],"ranking":[121],"tasks,":[122],"demonstrating":[123],"its":[124],"superiority":[125],"learning":[127],"generalizable":[128],"preference":[130],"patterns.":[131],"Building":[132],"this,":[134],"we":[135],"empirically":[136],"demonstrate,":[137],"first":[140],"time,":[141],"robust":[142],"power-law":[143],"an":[146],"LLM":[147,179],"is":[149],"continually":[150],"pre-trained":[151],"high-quality,":[154,196],"recommendation-specific":[155],"data.":[156],"Our":[157],"experiments":[158],"reveal":[159],"consistent":[160],"perplexity":[163],"reduction":[164],"across":[165],"multiple":[166],"modalities.":[169],"These":[170],"findings":[171],"establish":[172],"foundational":[174],"methodology":[175],"reliable":[177],"capabilities":[180],"recommendation":[183],"domain,":[184],"thereby":[185],"shifting":[186],"focus":[189],"from":[190],"mitigating":[191],"deficiencies":[193],"leveraging":[195],"structured":[197],"information.":[198]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-11T00:00:00"}