{"id":"https://openalex.org/W7127601237","doi":"https://doi.org/10.48550/arxiv.2602.02827","title":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","display_name":"Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval","publication_year":2026,"publication_date":"2026-02-02","ids":{"openalex":"https://openalex.org/W7127601237","doi":"https://doi.org/10.48550/arxiv.2602.02827"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2602.02827","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2602.02827","pdf_url":"https://arxiv.org/pdf/2602.02827","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2602.02827","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5096068527","display_name":"Roi Pony","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pony, Roi","raw_affiliation_strings":["IBM Research Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Israel","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069713654","display_name":"Adi Raz Goldfarb","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Goldfarb, Adi Raz","raw_affiliation_strings":["IBM Research Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Israel","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020146315","display_name":"Oshri Naparstek","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Naparstek, Oshri","raw_affiliation_strings":["IBM Research Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Israel","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043426411","display_name":"Idan Friedman","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Friedman, Idan","raw_affiliation_strings":["IBM Research Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Israel","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047102702","display_name":"Udi Barzelay","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Barzelay, Udi","raw_affiliation_strings":["IBM Research Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Israel","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122922191","display_name":"Eli Schwartz","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Schwartz, Eli","raw_affiliation_strings":["IBM Research Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Israel","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1341412227"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":0.9423999786376953,"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":0.9423999786376953,"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/T10028","display_name":"Topic Modeling","score":0.04500000178813934,"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/T11269","display_name":"Algorithms and Data Compression","score":0.002099999925121665,"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/colbert","display_name":"Colbert","score":0.9599999785423279},{"id":"https://openalex.org/keywords/bandit-algorithms","display_name":"bandit algorithms","score":0.531000018119812},{"id":"https://openalex.org/keywords/re-ranking","display_name":"re-ranking","score":0.8220000267028809},{"id":"https://openalex.org/keywords/multi-vector-retrieval","display_name":"multi-vector retrieval","score":0.5230000019073486}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7635999917984009},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6384000182151794},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5530999898910522},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5296000242233276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4796999990940094},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4438999891281128},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4327999949455261},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.40380001068115234},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.38760000467300415},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32350000739097595},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.3028999865055084},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29600000381469727},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27399998903274536},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.26420000195503235},{"id":"https://openalex.org/C167927819","wikidata":"https://www.wikidata.org/wiki/Q1930567","display_name":"Shuffling","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2602.02827","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2602.02827","pdf_url":"https://arxiv.org/pdf/2602.02827","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2602.02827","doi":"https://doi.org/10.48550/arxiv.2602.02827","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.02827","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2602.02827","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2602.02827","pdf_url":"https://arxiv.org/pdf/2602.02827","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/16","score":0.6515514850616455,"display_name":"Peace, justice, and strong institutions"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7127601237.pdf","grobid_xml":"https://content.openalex.org/works/W7127601237.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4226518707","https://openalex.org/W3034439313","https://openalex.org/W7223082383","https://openalex.org/W4400525755","https://openalex.org/W6979330229","https://openalex.org/W7167952531","https://openalex.org/W7141059085","https://openalex.org/W7166170780","https://openalex.org/W3021397474","https://openalex.org/W4281251078"],"abstract_inverted_index":{"Multi-vector":[0],"late-interaction":[1,44],"retrievers":[2],"such":[3],"as":[4],"ColBERT":[5],"achieve":[6],"state-of-the-art":[7],"quality,":[8],"but":[9],"their":[10],"query-time":[11,58],"cost":[12],"is":[13],"dominated":[14],"by":[15,146],"exhaustively":[16],"computing":[17,95],"token-level":[18],"MaxSim":[19,26,144],"interactions":[20],"for":[21,150],"every":[22,52,140],"candidate":[23],"document.":[24],"The":[25],"scores":[27],"of":[28,60],"$N$":[29],"candidates":[30],"against":[31],"$T$":[32],"query":[33],"tokens":[34],"form":[35],"an":[36],"$N\\times":[37],"T$":[38],"matrix":[39,66],"whose":[40,85],"row-sums":[41],"are":[42],"the":[43,48,61,90,97,102,110,136],"scores,":[45],"and":[46,80,128,159],"identifying":[47],"top-$K$":[49],"rarely":[50],"requires":[51],"entry.":[53],"We":[54,113],"introduce":[55],"Col-Bandit,":[56],"a":[57,71,119,123],"estimator":[59],"exhaustive-MaxSim":[62],"top-$K$:":[63],"it":[64,165],"reveals":[65],"entries":[67],"in":[68],"batches,":[69],"maintains":[70],"finite-population":[72],"Bernstein-Serfling":[73],"confidence":[74],"interval":[75],"on":[76,139],"each":[77],"candidate's":[78],"score,":[79],"permanently":[81],"drops":[82],"any":[83],"document":[84],"upper":[86],"bound":[87],"falls":[88],"below":[89],"$K$-th":[91],"largest":[92],"lower":[93],"bound,":[94],"only":[96],"cells":[98],"needed":[99],"to":[100,135,148,152],"separate":[101],"top-$K$.":[103],"A":[104,161],"single":[105],"relaxation":[106],"knob":[107],"$\u03b1_{\\mathrm{ef}}\\in(0,1]$":[108],"tunes":[109],"compute-fidelity":[111],"trade-off.":[112],"deploy":[114],"$\u03b1_{\\mathrm{ef}}{=}0.2$,":[115],"while":[116,142],"$\u03b1_{\\mathrm{ef}}{=}1$":[117],"admits":[118],"$\u03b4$-PAC":[120],"guarantee":[121],"under":[122],"simplified":[124],"radius.":[125],"On":[126],"BEIR":[127],"REAL-MM-RAG,":[129],"Col-Bandit":[130],"preserves":[131],"$\\geq":[132],"90\\%$":[133],"fidelity":[134],"exhaustive":[137],"top-$5$":[138],"corpus":[141],"cutting":[143],"FLOPs":[145],"up":[147,151],"${\\sim}8\\times$,":[149],"${\\sim}13\\times$":[153],"single-thread":[154],"CPU":[155],"speedups":[156],"across":[157],"x86":[158],"ARM.":[160],"drop-in":[162],"reranking":[163],"layer,":[164],"needs":[166],"no":[167],"retraining":[168],"or":[169],"index":[170],"changes.":[171]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-02-06T00:00:00"}