{"id":"https://openalex.org/W7166732823","doi":"https://doi.org/10.48550/arxiv.2606.28370","title":"Conversational Query Engine for Mixed-Modality Heterogeneous Enterprise Data Sources","display_name":"Conversational Query Engine for Mixed-Modality Heterogeneous Enterprise Data Sources","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7166732823","doi":"https://doi.org/10.48550/arxiv.2606.28370"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.28370","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28370","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.2606.28370","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060340303","display_name":"Darshita Rathore","orcid":"https://orcid.org/0000-0003-0430-1129"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rathore, Darshita","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100663902","display_name":"Vineet Kumar","orcid":"https://orcid.org/0000-0001-8364-3981"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kumar, Vineet","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139656363","display_name":"Vaibhav Singal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Singal, Vaibhav","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139687735","display_name":"Ankur Vivek Singh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Singh, Ankur Vivek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139702961","display_name":"Anindya Moitra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moitra, Anindya","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/T10317","display_name":"Advanced Database Systems and Queries","score":0.3628999888896942,"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"}},"topics":[{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.3628999888896942,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.12389999628067017,"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/T11719","display_name":"Data Quality and Management","score":0.10130000114440918,"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/query-language","display_name":"Query language","score":0.5360000133514404},{"id":"https://openalex.org/keywords/chunking","display_name":"Chunking (psychology)","score":0.4797999858856201},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.47119998931884766},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4269999861717224},{"id":"https://openalex.org/keywords/materialized-view","display_name":"Materialized view","score":0.37700000405311584},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.37119999527931213},{"id":"https://openalex.org/keywords/data-warehouse","display_name":"Data warehouse","score":0.35589998960494995},{"id":"https://openalex.org/keywords/xquery","display_name":"XQuery","score":0.32350000739097595},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.3199999928474426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8431000113487244},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.5360000133514404},{"id":"https://openalex.org/C203357204","wikidata":"https://www.wikidata.org/wiki/Q1089605","display_name":"Chunking (psychology)","level":2,"score":0.4797999858856201},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.47119998931884766},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3822000026702881},{"id":"https://openalex.org/C98199447","wikidata":"https://www.wikidata.org/wiki/Q2445044","display_name":"Materialized view","level":4,"score":0.37700000405311584},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C135572916","wikidata":"https://www.wikidata.org/wiki/Q193351","display_name":"Data warehouse","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C2780512708","wikidata":"https://www.wikidata.org/wiki/Q850661","display_name":"XQuery","level":4,"score":0.32350000739097595},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.31529998779296875},{"id":"https://openalex.org/C47487241","wikidata":"https://www.wikidata.org/wiki/Q5227230","display_name":"Data access","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C20277647","wikidata":"https://www.wikidata.org/wiki/Q5227234","display_name":"Data access layer","level":3,"score":0.3111000061035156},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C137877099","wikidata":"https://www.wikidata.org/wiki/Q1332977","display_name":"Subsequence","level":3,"score":0.29899999499320984},{"id":"https://openalex.org/C510870499","wikidata":"https://www.wikidata.org/wiki/Q47607","display_name":"SQL","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C118689300","wikidata":"https://www.wikidata.org/wiki/Q7978614","display_name":"Web query classification","level":4,"score":0.2793999910354614},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27239999175071716},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C27295321","wikidata":"https://www.wikidata.org/wiki/Q831795","display_name":"Enterprise information system","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C2767350","wikidata":"https://www.wikidata.org/wiki/Q6662173","display_name":"Business intelligence","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C136227091","wikidata":"https://www.wikidata.org/wiki/Q5380376","display_name":"Enterprise data management","level":3,"score":0.2531000077724457},{"id":"https://openalex.org/C192939062","wikidata":"https://www.wikidata.org/wiki/Q104840822","display_name":"Sargable","level":4,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.28370","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28370","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.2606.28370","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28370","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":{"Enterprise":[0],"business":[1],"intelligence":[2],"queries":[3],"span":[4],"structured":[5,88],"warehouses":[6],"and":[7,20,40,94,124,130,151,179],"unstructured":[8],"document":[9],"repositories":[10],"--":[11,79],"modalities":[12],"with":[13],"fundamentally":[14],"different":[15],"access":[16,44],"methods,":[17],"cost":[18,134],"profiles,":[19],"correctness":[21],"semantics.":[22],"Existing":[23],"AI-enabled":[24],"interfaces":[25],"force":[26],"users":[27],"to":[28,45],"select":[29],"the":[30],"right":[31],"tool:":[32],"NL2SQL":[33,146],"systems":[34],"cannot":[35],"reason":[36],"over":[37],"slide":[38],"decks,":[39],"RAG":[41],"pipelines":[42],"lack":[43],"live":[46],"warehouse":[47],"tables.":[48],"We":[49],"present":[50],"COGNI,":[51],"a":[52,62,106,111,118,138,144,162],"production":[53],"conversational":[54],"BI":[55],"system":[56],"that":[57,116],"treats":[58],"natural-language":[59],"analytics":[60],"as":[61,68,91],"heterogeneous":[63],"query":[64,166],"processing":[65],"problem,":[66],"organized":[67],"four":[69],"architectural":[70],"layers.":[71],"First,":[72],"an":[73],"indexing":[74],"layer":[75,108,140,164],"implements":[76],"slide-adaptive":[77],"chunking":[78,81,86],"recursive":[80],"for":[82,87],"plain-text":[83],"slides,":[84],"hierarchical":[85],"content":[89],"such":[90],"tables,":[92],"charts,":[93],"key-value":[95],"blocks":[96],"-":[97,121],"achieving":[98,174],"$88.3\\%$":[99],"on":[100,110,157],"our":[101],"internal":[102],"enterprise":[103],"benchmark.":[104],"Second,":[105],"routing":[107],"built":[109],"LoRA":[112],"fine-tuned":[113],"Qwen-2.5-1.5B-Instruct":[114],"model":[115],"produces":[117],"dual":[119],"output":[120],"modality":[122],"decision":[123],"complexity":[125],"assessment":[126],"at":[127,148],"$93.8\\%$":[128],"accuracy":[129],"approximately":[131],"$7\\times$":[132],"lower":[133],"than":[135],"frontier-model.":[136],"Third,":[137],"retrieval":[139],"executes":[141],"complexity-adaptive":[142],"pipelines:":[143],"self-correcting":[145],"agent":[147],"$93.9\\%$":[149],"G-Eval,":[150],"Recursive":[152],"Language":[153],"Models":[154],"reaching":[155],"$91.0\\%$":[156],"multi-hop":[158],"synthesis":[159],"queries.":[160],"Finally,":[161],"caching":[163],"validates":[165],"equivalence":[167],"across":[168],"multiple":[169],"dimensions":[170],"beyond":[171],"embedding":[172],"similarity,":[173],"zero":[175],"false":[176],"cache":[177],"hits":[178],"$8.4\\times$":[180],"latency":[181],"reduction.":[182]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}