{"id":"https://openalex.org/W7163215463","doi":"https://doi.org/10.48550/arxiv.2606.01670","title":"Time-Aware Diffusion based on Preference Disentanglement for Generative Recommendation","display_name":"Time-Aware Diffusion based on Preference Disentanglement for Generative Recommendation","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7163215463","doi":"https://doi.org/10.48550/arxiv.2606.01670"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.01670","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01670","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.2606.01670","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137703653","display_name":"Bangguo Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Bangguo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128659779","display_name":"Peng Huo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huo, Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125556938","display_name":"Yuanbo Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yuanbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137664511","display_name":"Zhicheng Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Zhicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137617898","display_name":"Jun Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Jun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137711784","display_name":"Senzhang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Senzhang","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/T10203","display_name":"Recommender Systems and Techniques","score":0.9732999801635742,"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":0.9732999801635742,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T13702","display_name":"Machine Learning in Healthcare","score":0.0015999999595806003,"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/generative-grammar","display_name":"Generative grammar","score":0.7335000038146973},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.6689000129699707},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.6496000289916992},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.5231000185012817},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.49129998683929443},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4334999918937683},{"id":"https://openalex.org/keywords/transformative-learning","display_name":"Transformative learning","score":0.413100004196167}],"concepts":[{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.7335000038146973},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.6689000129699707},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.6496000289916992},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6358000040054321},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.5231000185012817},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.49129998683929443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4422999918460846},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4334999918937683},{"id":"https://openalex.org/C70587473","wikidata":"https://www.wikidata.org/wiki/Q7834111","display_name":"Transformative learning","level":2,"score":0.413100004196167},{"id":"https://openalex.org/C68710425","wikidata":"https://www.wikidata.org/wiki/Q5275442","display_name":"Diffusion process","level":3,"score":0.3698999881744385},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3522000014781952},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.29159998893737793},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27239999175071716},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2703000009059906},{"id":"https://openalex.org/C2779433544","wikidata":"https://www.wikidata.org/wiki/Q1435226","display_name":"Focal point","level":3,"score":0.26420000195503235},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.258899986743927},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2574000060558319}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.01670","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01670","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.2606.01670","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01670","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"Generative":[1],"Recommenders":[2],"(GRs)":[3],"have":[4],"emerged":[5],"as":[6,39],"a":[7,29,43,78,92,136],"transformative":[8],"recommendation":[9],"paradigm":[10],"by":[11,71,98,147],"replacing":[12],"traditional":[13],"item":[14],"IDs":[15],"with":[16,36],"semantic":[17],"indices":[18],"(SIDs).":[19],"Owing":[20],"to":[21,57,174],"the":[22,40,52,61,66,82,100,110,117,122,129,141,159,165,190],"exceptional":[23],"generative":[24],"capabilities":[25],"of":[26,46,112,162,172,180,192],"diffusion":[27,37,53,102,118,195],"models,":[28],"few":[30],"pioneering":[31],"works":[32],"explore":[33],"developing":[34],"GRs":[35,49],"architectures":[38],"backbone.":[41],"However,":[42],"fatal":[44],"limitation":[45],"existing":[47],"diffusion-based":[48,197],"is":[50,69,125,145],"that":[51],"process":[54],"applies":[55],"uniformly":[56],"all":[58],"items":[59],"within":[60],"historical":[62],"interactions.":[63],"In":[64,120],"contrast,":[65],"user":[67,114,123],"preference":[68,124],"shaped":[70],"multifaceted":[72],"time-evolving":[73,113],"factors":[74],"and":[75,139,176,182],"thus":[76],"exhibits":[77],"non-stationary":[79],"distribution":[80],"in":[81,178,196],"temporal":[83],"aspect.":[84],"To":[85],"bridge":[86],"this":[87,89],"gap,":[88],"study":[90,187],"proposes":[91],"novel":[93],"GR":[94],"framework,":[95],"named":[96],"TDPM,":[97],"designing":[99],"time-aware":[101,193],"on":[103,153],"SID":[104],"tokens.":[105],"Specifically,":[106],"TDPM":[107,163,168],"explicitly":[108],"integrates":[109],"impact":[111],"preferences":[115],"into":[116,127],"process.":[119],"detail,":[121],"disentangled":[126],"(i)":[128],"period":[130],"preference,":[131,143],"which":[132,144],"remains":[133],"consistent":[134],"over":[135,164],"long":[137],"time-span,":[138],"(ii)":[140],"point":[142],"triggered":[146],"recent":[148],"focal":[149],"events.":[150],"Extensive":[151],"experiments":[152],"three":[154],"public":[155],"real-world":[156],"datasets":[157],"demonstrate":[158],"significant":[160],"superiority":[161],"state-of-the-art":[166],"baselines.":[167],"achieves":[169],"average":[170],"improvements":[171],"up":[173],"29.21%":[175],"25.45%":[177],"terms":[179],"HR@20":[181],"NDCG@20,":[183],"respectively.":[184],"The":[185],"ablation":[186],"further":[188],"underscores":[189],"necessity":[191],"token":[194],"GRs.":[198]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-03T00:00:00"}