{"id":"https://openalex.org/W7164801847","doi":"https://doi.org/10.48550/arxiv.2606.14193","title":"Revisiting Filtered ANN Benchmarks: A Hardness-Controlled Benchmark Generator for Realistic Evaluation","display_name":"Revisiting Filtered ANN Benchmarks: A Hardness-Controlled Benchmark Generator for Realistic Evaluation","publication_year":2026,"publication_date":"2026-06-12","ids":{"openalex":"https://openalex.org/W7164801847","doi":"https://doi.org/10.48550/arxiv.2606.14193"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.14193","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.14193","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.14193","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110993195","display_name":"Mintaek Lim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lim, Mintaek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132754878","display_name":"Dogeun Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Dogeun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138667700","display_name":"Minwoo Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Minwoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138663928","display_name":"Jaeyoung Do","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Do, Jaeyoung","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/T11719","display_name":"Data Quality and Management","score":0.426800012588501,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.426800012588501,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.10360000282526016,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0568000003695488,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6115000247955322},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5982999801635742},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.5322999954223633},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.4602999985218048},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4050000011920929},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.34299999475479126},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.32989999651908875},{"id":"https://openalex.org/keywords/toolbox","display_name":"Toolbox","score":0.31040000915527344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7398999929428101},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6115000247955322},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5982999801635742},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.5322999954223633},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4975999891757965},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4602999985218048},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4050000011920929},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3684999942779541},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36239999532699585},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.32989999651908875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3199999928474426},{"id":"https://openalex.org/C2777655017","wikidata":"https://www.wikidata.org/wiki/Q1501161","display_name":"Toolbox","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30000001192092896},{"id":"https://openalex.org/C3018790387","wikidata":"https://www.wikidata.org/wiki/Q869010","display_name":"Hybrid learning","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2678000032901764},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.14193","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.14193","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.14193","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.14193","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":"Preprint"},"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":{"Filtered":[0],"approximate":[1],"nearest":[2],"neighbor":[3],"(FANN)":[4],"search":[5],"must":[6],"satisfy":[7],"both":[8],"vector":[9],"similarity":[10],"and":[11,25,56,79,88,187],"structured":[12],"predicates,":[13],"yet":[14],"evaluations":[15],"remain":[16],"brittle":[17],"because":[18],"real":[19,188],"hybrid":[20,89],"workloads":[21,131,178],"are":[22,108],"rarely":[23],"shareable":[24],"existing":[26],"benchmarks":[27,149,186],"rely":[28],"on":[29,40,59],"ad-hoc":[30],"synthetic":[31],"or":[32,105,111,136],"semi-real":[33],"constructions.":[34],"We":[35,113],"argue":[36],"that":[37,69,121,146,163,171,179],"realism":[38],"hinges":[39],"execution-driven":[41],"query":[42],"difficulty:":[43],"failures":[44],"in":[45],"early":[46],"filtering":[47],"trigger":[48],"over-fetching":[49],"of":[50,156],"additional":[51],"candidates,":[52],"shaping":[53],"latency,":[54],"throughput,":[55],"recall.":[57],"Building":[58],"this":[60],"insight,":[61],"we":[62,169],"propose":[63],"$\u03b1$-Hardness,":[64],"a":[65,117,139,151],"query-level":[66],"hardness":[67,141,158,173],"metric":[68],"models":[70],"the":[71,76,157],"conditional":[72],"execution":[73],"chain":[74],"via":[75],"over-fetch":[77],"factor":[78],"extends":[80],"naturally":[81],"to":[82,129,137],"strategy-conditioned":[83],"settings.":[84],"Across":[85],"diverse":[86],"datasets":[87],"strategies,":[90],"$\u03b1$-Hardness":[91,123],"exhibits":[92],"strong":[93],"monotonic":[94],"alignment":[95],"with":[96],"empirical":[97],"performance,":[98],"while":[99],"common":[100],"proxies":[101],"such":[102],"as":[103,124],"selectivity":[104],"attribute-vector":[106],"correlation":[107],"frequently":[109],"unstable":[110],"strategy-inconsistent.":[112],"further":[114],"introduce":[115],"HCBGen,":[116],"hardness-controlled":[118],"benchmark":[119],"generator":[120],"uses":[122],"an":[125],"explicit":[126],"control":[127],"signal":[128],"synthesize":[130],"under":[132,165],"coarse":[133],"bias":[134],"modes":[135],"match":[138],"target":[140],"profile.":[142],"Our":[143],"experiments":[144],"show":[145],"widely":[147],"used":[148],"occupy":[150],"narrow,":[152],"relatively":[153],"easy":[154],"portion":[155],"spectrum,":[159],"masking":[160],"robustness":[161],"gaps":[162],"emerge":[164],"harder":[166],"queries.":[167],"Finally,":[168],"demonstrate":[170],"matching":[172],"distributions":[174],"enables":[175],"privacy-preserving":[176],"proxy":[177],"closely":[180],"reproduce":[181],"performance":[182],"trends,":[183],"bridging":[184],"research":[185],"evaluation.":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-16T00:00:00"}
