{"id":"https://openalex.org/W7150877218","doi":"https://doi.org/10.48550/arxiv.2604.02801","title":"Distance Comparison Operations Are Not Silver Bullets in Vector Similarity Search: A Benchmark Study on Their Merits and Limits","display_name":"Distance Comparison Operations Are Not Silver Bullets in Vector Similarity Search: A Benchmark Study on Their Merits and Limits","publication_year":2026,"publication_date":"2026-04-03","ids":{"openalex":"https://openalex.org/W7150877218","doi":"https://doi.org/10.48550/arxiv.2604.02801"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.02801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02801","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.2604.02801","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035025714","display_name":"Zhuanglin Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zheng, Zhuanglin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133016099","display_name":"Yuxiang Zeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Yuxiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133030061","display_name":"Chenchen Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Chenchen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133056808","display_name":"Yunzhen Chi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chi, Yunzhen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065763579","display_name":"Bo Yang","orcid":"https://orcid.org/0009-0008-1798-4268"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Binhan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133056524","display_name":"Yongxin Tong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong, Yongxin","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5035025714"],"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/T11106","display_name":"Data Management and Algorithms","score":0.535099983215332,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.535099983215332,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.19509999454021454,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11719","display_name":"Data Quality and Management","score":0.061900001019239426,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7548999786376953},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6621999740600586},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5508000254631042},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5419999957084656},{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.3262999951839447},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.30720001459121704},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.30660000443458557}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7548999786376953},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6621999740600586},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6137999892234802},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5608000159263611},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5508000254631042},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5419999957084656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4018000066280365},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.30660000443458557},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.274399995803833},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2578999996185303},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2513999938964844},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.02801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02801","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.2604.02801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02801","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Distance":[0],"Comparison":[1],"Operations":[2],"(DCOs),":[3],"which":[4,132],"decide":[5],"whether":[6],"the":[7],"distance":[8,35],"between":[9],"a":[10,14,18,21,57,137],"data":[11,100,124],"vector":[12,26,45],"and":[13,72,75,82,106,123],"query":[15],"is":[16,96,107],"within":[17],"threshold,":[19],"are":[20,90,150],"critical":[22],"performance":[23],"bottleneck":[24],"in":[25,148],"similarity":[27],"search.":[28],"Recent":[29],"DCO":[30,62,149],"methods":[31,89],"that":[32,87,144],"avoid":[33],"full-dimensional":[34,138],"computations":[36],"promise":[37],"significant":[38],"speedups,":[39],"but":[40],"their":[41,94,129],"readiness":[42],"for":[43,154],"production":[44,155],"database":[46],"systems":[47],"remains":[48],"an":[49],"open":[50],"question.":[51],"To":[52],"address":[53],"this,":[54],"we":[55],"conduct":[56],"comprehensive":[58],"benchmark":[59],"of":[60],"8":[61],"algorithms":[63],"across":[64,109],"10":[65],"datasets":[66],"(with":[67],"up":[68],"to":[69,99,142],"100M":[70],"vectors":[71],"12,288":[73],"dimensions)":[74],"diverse":[76],"hardware":[77],"configurations":[78],"(CPUs":[79],"with/without":[80],"SIMD,":[81],"GPUs).":[83],"Our":[84],"study":[85],"reveals":[86],"these":[88,127],"not":[91,151],"silver":[92],"bullets:":[93],"efficiency":[95],"highly":[97],"sensitive":[98],"dimensionality,":[101],"degrades":[102],"under":[103],"out-of-distribution":[104],"queries,":[105],"unstable":[108,130],"hardware.":[110],"Yet,":[111],"our":[112],"evaluation":[113],"also":[114],"demonstrates":[115],"often-overlooked":[116],"merits:":[117],"they":[118],"can":[119,133],"accelerate":[120],"index":[121],"construction":[122],"updates.":[125],"Despite":[126],"benefits,":[128],"performance,":[131],"be":[134],"slower":[135],"than":[136],"scan,":[139],"leads":[140],"us":[141],"conclude":[143],"recent":[145],"algorithmic":[146],"advancements":[147],"yet":[152],"ready":[153],"deployment.":[156]},"counts_by_year":[],"updated_date":"2026-04-07T06:06:30.997549","created_date":"2026-04-07T00:00:00"}
