{"id":"https://openalex.org/W7134058367","doi":"https://doi.org/10.48550/arxiv.2603.04689","title":"Generalizing Fair Top-$k$ Selection: An Integrative Approach","display_name":"Generalizing Fair Top-$k$ Selection: An Integrative Approach","publication_year":2026,"publication_date":"2026-03-05","ids":{"openalex":"https://openalex.org/W7134058367","doi":"https://doi.org/10.48550/arxiv.2603.04689"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.04689","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085083129","display_name":"Guangya Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Cai, Guangya","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5085083129"],"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.4848000109195709,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.4848000109195709,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.164000004529953,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.1412999927997589,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5825999975204468},{"id":"https://openalex.org/keywords/disadvantaged","display_name":"Disadvantaged","score":0.5483999848365784},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5414000153541565},{"id":"https://openalex.org/keywords/balance","display_name":"Balance (ability)","score":0.5012000203132629},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.3828999996185303},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.3091999888420105}],"concepts":[{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5825999975204468},{"id":"https://openalex.org/C2780623907","wikidata":"https://www.wikidata.org/wiki/Q106394435","display_name":"Disadvantaged","level":2,"score":0.5483999848365784},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5414000153541565},{"id":"https://openalex.org/C168031717","wikidata":"https://www.wikidata.org/wiki/Q1530280","display_name":"Balance (ability)","level":2,"score":0.5012000203132629},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47589999437332153},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4339999854564667},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.3828999996185303},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3336000144481659},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31700000166893005},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.314300000667572},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30379998683929443},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2669000029563904},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C177580056","wikidata":"https://www.wikidata.org/wiki/Q5611272","display_name":"Group testing","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.04689","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.04689","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.04689","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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.04689","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","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":{"Fair":[0],"top-$k$":[1,18],"selection,":[2],"which":[3,55],"ensures":[4],"appropriate":[5],"proportional":[6],"representation":[7],"of":[8,29,71,105,133,155,161],"members":[9],"from":[10,45],"minority":[11],"or":[12],"historically":[13],"disadvantaged":[14],"groups":[15,39,73,163],"among":[16],"the":[17,27,43,52,59,69,80,86,103,106,119,143,150,153,159,172,175,178],"selected":[19],"candidates,":[20],"has":[21],"drawn":[22],"significant":[23],"attention.":[24],"We":[25],"study":[26],"problem":[28,120],"finding":[30],"a":[31,46,76,97,127,140,191],"fair":[32,176],"(linear)":[33],"scoring":[34,48,180,194],"function":[35,195],"with":[36,222],"multiple":[37],"protected":[38,72,162],"while":[40],"also":[41,138,225],"minimizing":[42],"disparity":[44,63,170,186],"reference":[47,179],"function.":[49],"This":[50],"generalizes":[51],"prior":[53],"setup,":[54],"was":[56],"restricted":[57],"to":[58,148],"single-group":[60],"setting":[61],"without":[62],"minimization.":[64],"Previous":[65],"studies":[66],"imply":[67],"that":[68,93,100,118,204],"number":[70,160],"may":[74,101,121,189],"have":[75],"limited":[77],"impact":[78],"on":[79,219],"runtime":[81],"efficiency.":[82],"However,":[83,135],"driven":[84],"by":[85],"need":[87],"for":[88,126,152],"experimental":[89,223],"exploration,":[90],"we":[91,182],"find":[92],"this":[94,109],"implication":[95],"overlooks":[96],"critical":[98],"issue":[99,110],"affect":[102],"fairness":[104],"outcome.":[107],"Once":[108],"is":[111,164],"properly":[112],"considered,":[113],"our":[114,136,211],"hardness":[115,144],"analysis":[116,137],"shows":[117],"become":[122],"computationally":[123],"intractable":[124],"even":[125],"two-dimensional":[128],"dataset":[129],"and":[130,177,209,229],"small":[131,156,197],"values":[132],"$k$.":[134],"reveals":[139],"gap":[141],"in":[142],"barrier,":[145],"enabling":[146],"us":[147],"recover":[149],"efficiency":[151],"case":[154],"$k$":[157],"when":[158],"sufficiently":[165],"small.":[166],"Furthermore,":[167],"beyond":[168],"measuring":[169],"as":[171],"\"distance\"":[173],"between":[174],"functions,":[181],"introduce":[183],"an":[184],"alternative":[185],"measure$\\unicode{x2014}$utility":[187],"loss$\\unicode{x2014}$that":[188],"yield":[190],"more":[192],"stable":[193],"under":[196],"weight":[198],"perturbations.":[199],"Through":[200],"careful":[201],"engineering":[202],"trade-offs":[203],"balance":[205],"implementation":[206,230],"complexity,":[207],"robustness,":[208],"performance,":[210],"augmented":[212],"two-pronged":[213],"solution":[214],"demonstrates":[215],"strong":[216],"empirical":[217],"performance":[218],"real-world":[220],"datasets,":[221],"observations":[224],"informing":[226],"algorithm":[227],"design":[228],"decisions.":[231]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-03-07T00:00:00"}
