{"id":"https://openalex.org/W7140302177","doi":"https://doi.org/10.48550/arxiv.2603.23183","title":"Reasoning over Semantic IDs Enhances Generative Recommendation","display_name":"Reasoning over Semantic IDs Enhances Generative Recommendation","publication_year":2026,"publication_date":"2026-03-24","ids":{"openalex":"https://openalex.org/W7140302177","doi":"https://doi.org/10.48550/arxiv.2603.23183"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.23183","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23183","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":null,"license_id":null,"version":null,"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":"https://doi.org/10.48550/arxiv.2603.23183","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101902851","display_name":"Yingzhi He","orcid":"https://orcid.org/0000-0002-6753-5523"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"He, Yingzhi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130606718","display_name":"Yan Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Yan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101379649","display_name":"Junfei Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Junfei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130625511","display_name":"Yuxin Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yuxin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076171663","display_name":"Xiaoyu Kong","orcid":"https://orcid.org/0009-0004-1386-9394"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Xiaoyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130609898","display_name":"Chunxu Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Chunxu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130573872","display_name":"Xiang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130557996","display_name":"An Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, An","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130550470","display_name":"Tat-Seng Chua","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chua, Tat-Seng","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5101902851"],"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":0.2825999855995178,"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":0.2825999855995178,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.19830000400543213,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.12839999794960022,"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/interpretability","display_name":"Interpretability","score":0.8327999711036682},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6100000143051147},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5777999758720398},{"id":"https://openalex.org/keywords/reasoning-system","display_name":"Reasoning system","score":0.48489999771118164},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.4237000048160553},{"id":"https://openalex.org/keywords/psychology-of-reasoning","display_name":"Psychology of reasoning","score":0.400299996137619},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.3977999985218048},{"id":"https://openalex.org/keywords/automated-reasoning","display_name":"Automated reasoning","score":0.35569998621940613},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3479999899864197}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8327999711036682},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7249000072479248},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6100000143051147},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5777999758720398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5533999800682068},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.48489999771118164},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.4237000048160553},{"id":"https://openalex.org/C183521366","wikidata":"https://www.wikidata.org/wiki/Q7256422","display_name":"Psychology of reasoning","level":4,"score":0.400299996137619},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39800000190734863},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3977999985218048},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.35569998621940613},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3479999899864197},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.32010000944137573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3125999867916107},{"id":"https://openalex.org/C140843580","wikidata":"https://www.wikidata.org/wiki/Q840067","display_name":"Defeasible reasoning","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.2896000146865845},{"id":"https://openalex.org/C159032336","wikidata":"https://www.wikidata.org/wiki/Q2488768","display_name":"Non-monotonic logic","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.2614000141620636},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.23183","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23183","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.23183","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23183","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"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":{"Recent":[0],"advances":[1],"in":[2,68,160],"generative":[3,206,221],"recommendation":[4,12,174],"have":[5],"leveraged":[6],"pretrained":[7],"LLMs":[8],"by":[9,32,118,152],"formulating":[10],"sequential":[11],"as":[13],"autoregressive":[14],"generation":[15],"over":[16,49,77,116],"a":[17,33,55,110,153],"unified":[18],"token":[19],"space":[20],"comprising":[21],"language":[22],"tokens":[23,84,159],"and":[24,53,81,163,226],"itemic":[25,158],"identifiers,":[26],"where":[27],"each":[28],"item":[29,51],"is":[30,95],"represented":[31],"compact":[34],"sequence":[35],"of":[36,133,202,216],"discrete":[37],"tokens,":[38],"namely":[39],"Semantic":[40],"IDs":[41],"(SIDs).":[42],"This":[43],"SID-based":[44,205],"formulation":[45],"enables":[46],"efficient":[47],"decoding":[48],"large-scale":[50],"corpora":[52],"provides":[54],"natural":[56],"interface":[57],"for":[58,220],"LLM-based":[59],"recommenders":[60],"to":[61,89,97,122],"leverage":[62],"rich":[63],"world":[64],"knowledge.":[65],"Meanwhile,":[66],"breakthroughs":[67],"LLM":[69,125],"reasoning":[70,76,94,115,135,175,186,191,218],"motivate":[71],"reasoning-enhanced":[72],"recommendation,":[73,222],"yet":[74],"effective":[75,185],"SIDs":[78,117],"remains":[79],"underexplored":[80],"challenging.":[82],"Itemic":[83],"are":[85],"not":[86],"natively":[87],"meaningful":[88],"LLMs;":[90],"moreover,":[91],"recommendation-oriented":[92],"SID":[93],"hard":[96],"evaluate,":[98],"making":[99],"high-quality":[100],"supervision":[101],"scarce.":[102],"To":[103],"address":[104],"these":[105],"challenges,":[106],"we":[107],"propose":[108],"SIDReasoner,":[109],"two-stage":[111],"framework":[112],"that":[113],"elicits":[114],"strengthening":[119],"SID--language":[120],"alignment":[121,142],"unlock":[123],"transferable":[124],"reasoning,":[126],"rather":[127],"than":[128],"relying":[129],"on":[130,146,167,195],"large":[131,217],"amounts":[132],"recommendation-specific":[134],"traces.":[136],"Concretely,":[137],"SIDReasoner":[138,171],"first":[139],"enhances":[140],"SID-language":[141],"via":[143],"multi-task":[144],"training":[145],"an":[147],"enriched":[148],"SID-centered":[149],"corpus":[150],"synthesized":[151],"stronger":[154],"teacher":[155],"model,":[156],"grounding":[157],"diverse":[161],"semantic":[162],"behavioral":[164],"contexts.":[165],"Building":[166],"this":[168],"enhanced":[169],"alignment,":[170],"further":[172],"improves":[173],"through":[176],"outcome-driven":[177],"reinforced":[178],"optimization,":[179],"which":[180],"guides":[181],"the":[182,200,210,213],"model":[183],"toward":[184],"trajectories":[187],"without":[188],"requiring":[189],"explicit":[190],"annotations.":[192],"Extensive":[193],"experiments":[194],"three":[196],"real-world":[197],"datasets":[198],"demonstrate":[199],"effectiveness":[201],"our":[203],"reasoning-augmented":[204],"recommendation.":[207],"Beyond":[208],"accuracy,":[209],"results":[211],"highlight":[212],"broader":[214],"potential":[215],"models":[219],"including":[223],"improved":[224],"interpretability":[225],"cross-domain":[227],"generalization.":[228]},"counts_by_year":[],"updated_date":"2026-03-26T06:10:45.909354","created_date":"2026-03-26T00:00:00"}