{"id":"https://openalex.org/W7166833263","doi":"https://doi.org/10.48550/arxiv.2606.31808","title":"Large Databases Need Small, Open-Weight Language Models","display_name":"Large Databases Need Small, Open-Weight Language Models","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7166833263","doi":"https://doi.org/10.48550/arxiv.2606.31808"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.31808","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31808","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,"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":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.2606.31808","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139799004","display_name":"Parker Glenn","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Glenn, Parker","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5066674792","display_name":"Alfy Samuel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samuel, Alfy","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/T10181","display_name":"Natural Language Processing Techniques","score":0.685699999332428,"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"}},"topics":[{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.685699999332428,"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/T14347","display_name":"Big Data and Digital Economy","score":0.036400001496076584,"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":0.03020000085234642,"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/context","display_name":"Context (archaeology)","score":0.573199987411499},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5680000185966492},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.531499981880188},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5248000025749207},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5034000277519226},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.47189998626708984},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.461899995803833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8177000284194946},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.573199987411499},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5680000185966492},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.531499981880188},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5248000025749207},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.519599974155426},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5034000277519226},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.47189998626708984},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.461899995803833},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.36550000309944153},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C40207289","wikidata":"https://www.wikidata.org/wiki/Q755662","display_name":"Relational model","level":3,"score":0.32019999623298645},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.314300000667572},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3012000024318695},{"id":"https://openalex.org/C45874996","wikidata":"https://www.wikidata.org/wiki/Q37045","display_name":"Markup language","level":3,"score":0.2903999984264374},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2815999984741211},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.2703999876976013}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.31808","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31808","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,"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.31808","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31808","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,"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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Language":[0],"model":[1],"systems":[2],"built":[3],"around":[4],"proprietary":[5,138],"APIs":[6,86],"often":[7],"operate":[8],"on":[9,56],"a":[10,34,74,124,137],"token-based":[11],"cost":[12],"model.":[13],"This":[14],"becomes":[15],"prohibitively":[16],"expensive":[17],"in":[18,127,133],"the":[19,65,77,80,97,118],"context":[20],"of":[21,37,59,67,76],"large":[22],"databases,":[23],"where":[24],"LM-enhanced":[25],"relational":[26],"operators":[27],"can":[28,61],"incur":[29],"costs":[30,129],"exceeding":[31],"$10,000":[32],"for":[33,89],"single":[35],"set":[36],"experiments,":[38],"hindering":[39],"thorough":[40],"research":[41],"and":[42,73,95,130],"practical":[43],"deployment.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48,122],"demonstrate":[49,123],"that":[50,83],"quantized,":[51],"open-weight":[52,106],"models":[53,107,116],"running":[54],"locally":[55],"just":[57],"16GB":[58],"VRAM":[60],"match":[62],"or":[63],"exceed":[64],"accuracy":[66],"closed-source":[68,84],"counterparts":[69],"at":[70,146],"lower":[71],"latency":[72,134],"fraction":[75],"price,":[78],"challenging":[79],"prevailing":[81],"assumption":[82],"LM":[85,139],"are":[87],"necessary":[88],"effective":[90],"LM-database":[91],"integration.":[92],"We":[93,141],"present":[94],"analyze":[96],"key":[98],"system":[99],"optimizations":[100],"required":[101],"to":[102,136],"efficiently":[103],"deploy":[104],"these":[105,114],"within":[108],"an":[109],"LM-DB":[110],"system.":[111],"By":[112],"integrating":[113],"local":[115],"into":[117],"BlendSQL":[119],"v0.1.0":[120],"framework,":[121],"390x":[125],"reduction":[126,132],"overall":[128],"3.8x":[131],"compared":[135],"API.":[140],"make":[142],"our":[143],"code":[144],"available":[145],"https://github.com/CapitalOne-Research/play-by-the-type-rules/tree/main/sembench.":[147]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-02T00:00:00"}
