{"id":"https://openalex.org/W7138207853","doi":"https://doi.org/10.48550/arxiv.2603.14422","title":"MBD: A Model-Based Debiasing Framework Across User, Content, and Model Dimensions","display_name":"MBD: A Model-Based Debiasing Framework Across User, Content, and Model Dimensions","publication_year":2026,"publication_date":"2026-03-15","ids":{"openalex":"https://openalex.org/W7138207853","doi":"https://doi.org/10.48550/arxiv.2603.14422"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.14422","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14422","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.2603.14422","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025890933","display_name":"Yuantong Li","orcid":"https://orcid.org/0000-0001-7420-2332"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li, Yuantong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129726457","display_name":"Lei Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012752468","display_name":"Zhihao Zheng","orcid":"https://orcid.org/0009-0006-5657-6916"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Zhihao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067459781","display_name":"Weimiao Wu","orcid":"https://orcid.org/0000-0001-6348-619X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Weimiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126503332","display_name":"Songbin Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Songbin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lee, Jeong Min","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Jeong Min","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088639036","display_name":"Ali Selman Aydin","orcid":"https://orcid.org/0000-0001-6958-6001"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aydin, Ali Selman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129666978","display_name":"Shaofeng Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Shaofeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129692188","display_name":"Junbo Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Junbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129674016","display_name":"Xinyi Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xinyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010165746","display_name":"Hongjing Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Hongjing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129702853","display_name":"Sam Fieldman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fieldman, Sam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129682629","display_name":"Matthew Kosko","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kosko, Matthew","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129707095","display_name":"Wei Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129705154","display_name":"Du Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Du","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014821337","display_name":"Peiyu Yang","orcid":"https://orcid.org/0000-0002-3827-8476"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Peiyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110810557","display_name":"Albert Jin Chung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chung, Albert Jin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129681860","display_name":"Xianlei Qiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Xianlei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129642668","display_name":"Miao Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Miao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053454559","display_name":"Zhongwei Teng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Teng, Zhongwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129680137","display_name":"Hao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129744469","display_name":"Sunny Baek","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baek, Sunny","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129679640","display_name":"Hui Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Hui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103868907","display_name":"Yang Lv","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lv, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033347744","display_name":"Renze Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Renze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129692618","display_name":"Qifan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Qifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129748646","display_name":"Zhan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123937519","display_name":"Tiantian Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Tiantian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129664808","display_name":"Peng Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129672695","display_name":"Ji Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Ji","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":30,"corresponding_author_ids":["https://openalex.org/A5025890933"],"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":0.7059999704360962,"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":0.7059999704360962,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.05829999968409538,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.031300000846385956,"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/debiasing","display_name":"Debiasing","score":0.8439000248908997},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5907999873161316},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.5188000202178955},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4961000084877014},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41909998655319214},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4187000095844269},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4154999852180481},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.4092000126838684}],"concepts":[{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.8439000248908997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7103999853134155},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5907999873161316},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.5188000202178955},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4961000084877014},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41909998655319214},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4154999852180481},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.4092000126838684},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.40119999647140503},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.3968000113964081},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3529999852180481},{"id":"https://openalex.org/C122048520","wikidata":"https://www.wikidata.org/wiki/Q2913954","display_name":"Percentile","level":2,"score":0.3522999882698059},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3384000062942505},{"id":"https://openalex.org/C122342681","wikidata":"https://www.wikidata.org/wiki/Q330828","display_name":"Skewness","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.31439998745918274},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3001999855041504},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C78639753","wikidata":"https://www.wikidata.org/wiki/Q3318160","display_name":"Behavioral modeling","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C75455068","wikidata":"https://www.wikidata.org/wiki/Q1455566","display_name":"Frequentist probability","level":3,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.14422","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14422","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.2603.14422","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14422","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/9","score":0.6508615016937256,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modern":[0],"recommendation":[1],"systems":[2],"rank":[3],"candidates":[4],"by":[5,22,143],"aggregating":[6],"multiple":[7],"behavioral":[8,109],"signals":[9,18,110,196,206],"through":[10],"a":[11,68,80,104,118,133,152,245],"value":[12,54,89,217],"model.":[13,218],"However,":[14],"many":[15],"commonly":[16],"used":[17],"are":[19,126],"inherently":[20],"affected":[21],"heterogeneous":[23],"biases.":[24],"For":[25],"example,":[26],"watch":[27],"time":[28],"naturally":[29],"favors":[30,35,43],"long-form":[31],"content,":[32,39],"loop":[33],"rate":[34],"short":[36],"-":[37,65,120,212],"form":[38],"and":[40,85,95,129,166,226,237],"comment":[41],"probability":[42,73],"videos":[44],"over":[45],"images.":[46],"Such":[47],"biases":[48],"introduce":[49],"two":[50],"critical":[51],"issues:":[52],"(1)":[53],"model":[55],"scores":[56],"may":[57,74],"be":[58,111],"systematically":[59,112],"misaligned":[60],"with":[61,146],"users'":[62],"relative":[63],"preferences":[64],"for":[66,79,172,215],"instance,":[67],"seemingly":[69],"low":[70],"absolute":[71],"like":[72],"represent":[75],"exceptionally":[76],"strong":[77],"interest":[78],"user":[81,119,180],"who":[82],"rarely":[83],"engages;":[84],"(2)":[86],"changes":[87],"in":[88],"modeling":[90,238],"rules":[91],"can":[92,107],"trigger":[93],"abrupt":[94],"undesirable":[96],"ecosystem":[97],"shifts.":[98],"In":[99],"this":[100,141,241],"work,":[101],"we":[102,160],"ask":[103],"fundamental":[105],"question:":[106],"biased":[108,194],"transformed":[113],"into":[114,197],"unbiased":[115,198],"signals,":[116],"under":[117],"defined":[121],"notion":[122],"of":[123,155,168,203,222,249],"``unbiasedness'',":[124],"that":[125,139],"both":[127],"personalized":[128],"adaptive?":[130],"We":[131],"propose":[132],"general,":[134],"model-based":[135],"debiasing":[136],"(MBD)":[137],"framework":[138,191],"addresses":[140],"challenge":[142],"augmenting":[144],"it":[145],"distributional":[147],"modeling.":[148],"By":[149],"conditioning":[150],"on":[151],"flexible":[153,225],"subset":[154],"features":[156],"(partial":[157],"feature":[158],"set),":[159],"explicitly":[161],"estimate":[162],"the":[163,169,184,190,201,216,220,229,250],"contextual":[164],"mean":[165],"variance":[167],"engagement":[170],"distribution":[171],"arbitrary":[173],"cohorts":[174],"(e.g.,":[175],"specific":[176],"video":[177],"lengths":[178],"or":[179,210],"regions)":[181],"directly":[182],"alongside":[183],"main":[185],"prediction.":[186],"This":[187],"integration":[188],"allows":[189],"to":[192,231,233],"convert":[193],"raw":[195],"representations,":[199],"enabling":[200],"construction":[202],"higher-level,":[204],"calibrated":[205],"(such":[207],"as":[208,244],"percentiles":[209],"z":[211],"scores)":[213],"suitable":[214],"Importantly,":[219],"definition":[221],"unbiasedness":[223],"is":[224,242],"controllable,":[227],"allowing":[228],"system":[230],"adapt":[232],"different":[234],"personalization":[235],"objectives":[236],"preferences.":[239],"Crucially,":[240],"implemented":[243],"lightweight,":[246],"built-in":[247],"branch":[248],"existing":[251],"MTML":[252],"ranking":[253],"model,":[254],"requiring":[255],"no":[256],"separate":[257],"serving":[258],"infrastructure.":[259]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-03-18T00:00:00"}