{"id":"https://openalex.org/W7166697027","doi":"https://doi.org/10.48550/arxiv.2606.29968","title":"CLIP: Lightweight Cosine-Law-Based Inverted-List Pruning for IVF-Based Vector Search","display_name":"CLIP: Lightweight Cosine-Law-Based Inverted-List Pruning for IVF-Based Vector Search","publication_year":2026,"publication_date":"2026-06-29","ids":{"openalex":"https://openalex.org/W7166697027","doi":"https://doi.org/10.48550/arxiv.2606.29968"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.29968","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29968","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.2606.29968","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134947889","display_name":"Y Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yitong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011276433","display_name":"Shuhang Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Shuhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113903386","display_name":"X J Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Xuanhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056795737","display_name":"P Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Pengcheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139642206","display_name":"Jianliang Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Jianliang","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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.6011999845504761,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.6011999845504761,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.12219999730587006,"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/T11106","display_name":"Data Management and Algorithms","score":0.08969999849796295,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.8711000084877014},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.501800000667572},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4074000120162964},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.40310001373291016},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.34610000252723694},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.34139999747276306},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.3325999975204468},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.32440000772476196}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8711000084877014},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7882000207901001},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.501800000667572},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4074000120162964},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3986000120639801},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.34610000252723694},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3325999975204468},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.296099990606308},{"id":"https://openalex.org/C2777851325","wikidata":"https://www.wikidata.org/wiki/Q7094102","display_name":"Online model","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C167927819","wikidata":"https://www.wikidata.org/wiki/Q1930567","display_name":"Shuffling","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C130590232","wikidata":"https://www.wikidata.org/wiki/Q1671754","display_name":"Inverted index","level":3,"score":0.2903999984264374},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27469998598098755},{"id":"https://openalex.org/C24028149","wikidata":"https://www.wikidata.org/wiki/Q7094056","display_name":"Online aggregation","level":5,"score":0.2612999975681305},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26080000400543213},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.29968","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29968","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.2606.29968","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29968","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7794632911682129}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Vector":[0],"search":[1],"has":[2],"become":[3],"a":[4,90,143,168],"core":[5],"component":[6],"of":[7,83,117,132],"modern":[8],"multimodal":[9],"retrieval":[10],"systems.":[11],"Among":[12],"existing":[13],"methods,":[14],"inverted":[15],"file":[16],"(IVF)-based":[17],"methods":[18],"are":[19,33],"widely":[20],"adopted":[21],"due":[22,79],"to":[23,80,193,216,233],"their":[24],"scalability,":[25],"efficient":[26,198],"updates,":[27],"and":[28,45,75,99,106,129,162,196,219],"hardware":[29],"friendliness.":[30],"However,":[31],"they":[32,65],"fundamentally":[34],"limited":[35],"by":[36,189,231],"coarse-grained":[37],"execution:":[38],"each":[39],"query":[40,55],"typically":[41],"probes":[42],"many":[43],"clusters":[44],"exhaustively":[46],"scans":[47],"all":[48],"vectors":[49,134],"within":[50],"them,":[51],"resulting":[52],"in":[53,126,135,138],"high":[54],"latency.":[56],"Prior":[57],"works":[58],"mitigate":[59],"this":[60],"using":[61],"pruning":[62,70,84,93,218],"strategies,":[63],"but":[64],"often":[66],"incur":[67],"substantial":[68],"extra":[69],"overhead,":[71],"lack":[72],"cluster-level":[73],"pruning,":[74,101],"compromise":[76],"update":[77,241],"efficiency":[78,222],"heavy":[81],"maintenance":[82,192],"metadata.":[85],"This":[86],"paper":[87],"proposes":[88],"CLIP,":[89],"lightweight":[91],"cosine-law-based":[92,118],"technique":[94],"that":[95,185,203,211],"supports":[96,186],"both":[97],"inter-":[98],"intra-cluster":[100],"substantially":[102],"reducing":[103],"unnecessary":[104],"cluster":[105,125],"vector":[107],"accesses":[108],"with":[109,142,167,239],"negligible":[110],"overhead.":[111],"First,":[112],"CLIP":[113,159,212],"exploits":[114],"the":[115,139],"monotonicity":[116],"lower":[119],"bounds,":[120],"enabling":[121],"eliminating":[122],"an":[123,182],"undesirable":[124],"O(1)":[127],"time":[128,137],"filtering":[130],"batches":[131],"irrelevant":[133],"logarithmic":[136],"list":[140],"size,":[141],"tight":[144],"analytical":[145],"guarantee.":[146],"Second,":[147],"building":[148],"on":[149],"this,":[150],"we":[151,179],"develop":[152],"two":[153],"IVF":[154,225,237],"variants:":[155],"IVF-CLIP,":[156],"which":[157,164],"integrates":[158],"into":[160],"IVFFlat,":[161],"HIVF-CLIP,":[163],"extends":[165],"it":[166],"hierarchical":[169],"structure":[170],"for":[171,176],"adaptive":[172],"sub-cluster":[173],"probing.":[174],"Third,":[175],"dynamic":[177,236],"workloads,":[178],"present":[180],"LSM-IVF,":[181],"LSM-inspired":[183],"design":[184],"fast":[187],"updates":[188],"deferring":[190],"index":[191],"background":[194],"compaction,":[195],"enables":[197],"queries":[199],"via":[200],"CLIP-based":[201],"optimizations":[202],"eliminate":[204],"costly":[205],"level-by-level":[206],"searches.":[207],"Extensive":[208],"experiments":[209],"show":[210],"variants":[213],"achieve":[214],"up":[215,232],"78%":[217],"69%":[220],"higher":[221],"over":[223,235],"static":[224],"baselines,":[226],"while":[227],"LSM-IVF":[228],"improves":[229],"throughput":[230],"141%":[234],"baselines":[238],"comparable":[240],"efficiency.":[242]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}
