{"id":"https://openalex.org/W7161851447","doi":"https://doi.org/10.48550/arxiv.2605.19651","title":"Divergence Meets Consensus: A Multi-Source Negative Sampling Framework for Sequential Recommendation","display_name":"Divergence Meets Consensus: A Multi-Source Negative Sampling Framework for Sequential Recommendation","publication_year":2026,"publication_date":"2026-05-19","ids":{"openalex":"https://openalex.org/W7161851447","doi":"https://doi.org/10.48550/arxiv.2605.19651"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.19651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19651","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.2605.19651","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136542686","display_name":"Yuanzi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yuanzi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136569706","display_name":"Lingjie Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lingjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136562631","display_name":"Jingyu Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Jingyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108891390","display_name":"Zihang Tian","orcid":"https://orcid.org/0009-0009-8292-5384"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian, Zihang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136508289","display_name":"Yuhan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136548392","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0002-5209-8295"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136518380","display_name":"Xu Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"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":0.7803000211715698,"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":0.7803000211715698,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.030700000002980232,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.01850000023841858,"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/divergence","display_name":"Divergence (linguistics)","score":0.7149999737739563},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.7088000178337097},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5465999841690063},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.38420000672340393},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.37770000100135803},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.34689998626708984},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.34310001134872437}],"concepts":[{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.7149999737739563},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7088000178337097},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6851000189781189},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5465999841690063},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.512499988079071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4846999943256378},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4471000134944916},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.38420000672340393},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.34689998626708984},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.34310001134872437},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.34130001068115234},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3262999951839447},{"id":"https://openalex.org/C113336015","wikidata":"https://www.wikidata.org/wiki/Q574010","display_name":"Complete information","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C75917345","wikidata":"https://www.wikidata.org/wiki/Q2725298","display_name":"Sampling bias","level":3,"score":0.2660999894142151},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.19651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19651","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.2605.19651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19651","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":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5559248328208923}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Negative":[0,101],"sampling":[1,36,58,162,199],"is":[2],"significant":[3],"for":[4,100],"training":[5],"sequential":[6],"recommendation":[7],"models":[8,138,159,191],"under":[9],"implicit":[10],"feedback.":[11],"The":[12,116],"predominant":[13],"strategy,":[14],"self-guided":[15],"hard":[16,75],"negative":[17,76,142,198],"sampling,":[18],"selects":[19],"negatives":[20],"based":[21],"on":[22,53,184],"the":[23,33,46,64,79,146,168,172],"model's":[24],"current":[25,54],"state":[26],"but":[27],"suffers":[28],"from":[29],"three":[30,120],"limitations:":[31],"(1)":[32],"coupling":[34],"between":[35,155],"and":[37,69,127,135,144,157,188,204],"model":[38,47,55,170],"updates":[39],"triggers":[40],"a":[41,60,74,103],"vicious":[42],"cycle":[43],"that":[44,193],"drives":[45],"into":[48],"local":[49],"optima;":[50],"(2)":[51],"relying":[52],"parameters":[56],"narrows":[57],"to":[59,139,160],"small":[61],"region":[62],"of":[63,111],"item":[65],"space,":[66],"reducing":[67],"diversity":[68],"harming":[70],"generalization;":[71],"(3)":[72],"identifying":[73],"requires":[77],"scoring":[78,132],"entire":[80],"candidate":[81],"pool,":[82],"causing":[83],"substantial":[84],"computational":[85,179],"overhead":[86],"with":[87,171],"minimal":[88],"information":[89],"gain.":[90],"To":[91],"address":[92],"these":[93],"challenges,":[94],"we":[95],"propose":[96],"MDCNS":[97,194],"(Multi-source":[98],"Divergence-Consensus":[99],"Sampling),":[102],"novel":[104],"\"Teacher-Peer-Self\"":[105],"framework":[106],"inspired":[107],"by":[108],"Vygotsky's":[109],"Zone":[110],"Proximal":[112],"Development":[113],"(ZPD)":[114],"theory.":[115],"proposed":[117],"method":[118],"comprises":[119],"components,":[121],"including":[122],"multi-source":[123,131],"scoring,":[124],"divergence":[125,150],"re-ranking,":[126],"consensus":[128,165],"distillation.":[129],"Firstly,":[130],"incorporates":[133],"peer":[134,158],"ensemble":[136],"teacher":[137,173],"inject":[140],"external":[141],"signals":[143],"break":[145],"self-reinforcement":[147],"loop.":[148],"Then,":[149],"re-ranking":[151],"exploits":[152],"prediction":[153],"discrepancy":[154],"self":[156,169],"enhance":[161],"diversity.":[163],"Finally,":[164],"distillation":[166],"aligns":[167],"via":[174],"KL":[175],"divergence,":[176],"simultaneously":[177],"improving":[178],"cost":[180],"utilization.":[181],"Extensive":[182],"experiments":[183],"six":[185],"real-world":[186],"datasets":[187],"five":[189],"backbone":[190],"show":[192],"consistently":[195],"outperforms":[196],"state-of-the-art":[197],"methods,":[200],"demonstrating":[201],"strong":[202],"effectiveness":[203],"generalization.":[205]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-21T00:00:00"}
