{"id":"https://openalex.org/W7224085385","doi":"https://doi.org/10.48550/arxiv.2610.37584","title":"REGER: Modeling inter-item Relations with Semantic IDs for Generative Recommendation","display_name":"REGER: Modeling inter-item Relations with Semantic IDs for Generative Recommendation","publication_year":2026,"publication_date":"2026-10-27","ids":{"openalex":"https://openalex.org/W7224085385","doi":"https://doi.org/10.48550/arxiv.2610.37584"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.37584","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.37584","pdf_url":"https://arxiv.org/pdf/2610.37584","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.37584","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5160043303","display_name":"Yuxi Huang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huang, Yuxi","raw_affiliation_strings":["University of Electronic Science and Technology of China Chengdu , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China Chengdu , China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075420567","display_name":"Silin Zhou","orcid":"https://orcid.org/0009-0006-2889-8862","observed_orcids":["https://orcid.org/0009-0006-2889-8862"]},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhou, Silin","raw_affiliation_strings":["University of Electronic Science and Technology of China Chengdu , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China Chengdu , China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012304143","display_name":"Chenhao Wang","orcid":"https://orcid.org/0000-0002-2681-4593","observed_orcids":["https://orcid.org/0000-0002-2681-4593"]},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang, Chenhao","raw_affiliation_strings":["University of Electronic Science and Technology of China Chengdu , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China Chengdu , China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160042875","display_name":"Zihan Li","orcid":"https://orcid.org/0009-0005-7090-7825","observed_orcids":["https://orcid.org/0009-0005-7090-7825"]},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li, Zihan","raw_affiliation_strings":["University of Electronic Science and Technology of China Chengdu , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China Chengdu , China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071663513","display_name":"\u90ed\u521a\u660e","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guo, Gangming","raw_affiliation_strings":["University of Electronic Science and Technology of China Chengdu , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China Chengdu , China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091491018","display_name":"Pei Ke","orcid":"https://orcid.org/0000-0001-7554-5636","observed_orcids":["https://orcid.org/0000-0001-7554-5636"]},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke, Pei","raw_affiliation_strings":["University of Electronic Science and Technology of China Chengdu , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China Chengdu , China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160051777","display_name":"Shen Gao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gao, Shen","raw_affiliation_strings":["University of Electronic Science and Technology of China Chengdu , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China Chengdu , China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102754146","display_name":"Shuo Shang","orcid":"https://orcid.org/0000-0002-1117-2890","observed_orcids":["https://orcid.org/0000-0002-1117-2890"]},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shang, Shuo","raw_affiliation_strings":["University of Electronic Science and Technology of China Chengdu , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China Chengdu , China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":1.0,"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":1.0,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.0,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generative-recommendation","display_name":"generative recommendation","score":0.9959999918937683},{"id":"https://openalex.org/keywords/semantic-ids","display_name":"semantic IDs","score":0.9190000295639038},{"id":"https://openalex.org/keywords/teacher-student-knowledge-distillation","display_name":"teacher-student distillation","score":0.6990000009536743},{"id":"https://openalex.org/keywords/prefix-tree","display_name":"prefix tree","score":0.5040000081062317},{"id":"https://openalex.org/keywords/personalized-recommendation","display_name":"personalized recommendation","score":0.8190000057220459}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7800999879837036},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5185999870300293},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5180000066757202},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.506600022315979},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5026000142097473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5013999938964844},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5008000135421753},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4966000020503998},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.45249998569488525},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.4449000060558319},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4361000061035156},{"id":"https://openalex.org/C37926939","wikidata":"https://www.wikidata.org/wiki/Q7449061","display_name":"Semantic equivalence","level":4,"score":0.4018999934196472},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.39629998803138733},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3797000050544739},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.37040001153945923},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.34060001373291016},{"id":"https://openalex.org/C2778828372","wikidata":"https://www.wikidata.org/wiki/Q5283209","display_name":"Distributional semantics","level":3,"score":0.3237999975681305},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.3125},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C110903229","wikidata":"https://www.wikidata.org/wiki/Q7449064","display_name":"Semantic integration","level":4,"score":0.30630001425743103},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2897999882698059},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.25690001249313354}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.37584","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.37584","pdf_url":"https://arxiv.org/pdf/2610.37584","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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.2610.37584","doi":"https://doi.org/10.48550/arxiv.2610.37584","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.37584","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.37584","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.37584","pdf_url":"https://arxiv.org/pdf/2610.37584","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7224085385.pdf","grobid_xml":"https://content.openalex.org/works/W7224085385.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7160634010","https://openalex.org/W7156045069","https://openalex.org/W7220729621","https://openalex.org/W7128511275","https://openalex.org/W7171722072","https://openalex.org/W7214275318","https://openalex.org/W7221363032","https://openalex.org/W7196969120","https://openalex.org/W7202173346","https://openalex.org/W7196997908"],"abstract_inverted_index":{"Personalized":[0],"recommendation":[1,18],"depends":[2],"on":[3,172,204],"learning":[4,109],"semantic":[5,28,50,85,99,106,112],"and":[6,14,39,66,89,130,159,214],"collaborative":[7,57,156],"relations":[8,51,58,83],"among":[9],"items":[10],"from":[11,43],"online":[12],"content":[13],"user":[15],"interactions.":[16],"Generative":[17],"(GR)":[19],"offers":[20],"a":[21,76,139,160,177],"promising":[22],"paradigm":[23],"by":[24,108],"autoregressively":[25],"generating":[26],"discrete":[27],"IDs":[29],"(SIDs)":[30],"of":[31,155,163,218],"items.":[32,135],"However,":[33],"randomly":[34],"initialized":[35],"SID":[36,90,124,148,194],"token":[37],"embeddings":[38],"GR":[40,95,212],"models":[41],"trained":[42],"scratch":[44],"do":[45],"not":[46],"directly":[47],"inherit":[48,104],"the":[49,94,147,192,216,219],"inherent":[52],"in":[53],"items,":[54],"while":[55],"inter-item":[56,82,105],"are":[59],"learned":[60],"largely":[61],"implicitly":[62],"through":[63,97],"token-level":[64],"attention":[65,118,121],"next-token":[67],"supervision.":[68],"To":[69],"address":[70],"this":[71,173,198],"limitation,":[72],"we":[73,175],"propose":[74],"REGER,":[75],"unified":[77],"framework":[78,141],"that":[79],"explicitly":[80],"incorporates":[81],"into":[84,167],"pretraining,":[86],"history":[87],"encoding,":[88],"generation.":[91],"We":[92,115,136],"pretrain":[93],"model":[96],"generative":[98],"retrieval,":[100],"enabling":[101],"it":[102],"to":[103,110,126],"similarity":[107],"generate":[111],"neighbors'":[113],"SIDs.":[114],"combine":[116],"global":[117],"with":[119,123,200],"local":[120],"aligned":[122],"boundaries":[125],"capture":[127],"historical":[128],"context":[129],"directed":[131],"transitions":[132],"between":[133],"adjacent":[134],"further":[137],"develop":[138],"theoretical":[140],"for":[142],"hierarchical":[143],"preference":[144,157,221],"decomposition":[145,162],"over":[146,183,210],"prefix":[149],"tree,":[150],"proving":[151],"an":[152],"exact":[153],"factorization":[154],"distributions":[158,182],"weighted":[161],"item-level":[164],"KL":[165,169],"divergence":[166],"prefix-conditional":[168],"divergences.":[170],"Building":[171],"analysis,":[174],"distill":[176],"discriminative":[178],"teacher's":[179],"full":[180],"conditional":[181],"all":[184],"legal":[185],"next":[186],"tokens":[187],"at":[188],"ground-truth":[189],"prefixes":[190],"along":[191],"target":[193],"path,":[195],"jointly":[196],"optimizing":[197],"objective":[199],"cross-entropy.":[201],"Extensive":[202],"experiments":[203],"real-world":[205],"datasets":[206],"demonstrate":[207],"consistent":[208],"improvements":[209],"existing":[211],"baselines":[213],"support":[215],"effectiveness":[217],"proposed":[220],"distillation.":[222]},"counts_by_year":[],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2026-10-29T00:00:00"}
