{"id":"https://openalex.org/W7134820642","doi":"https://doi.org/10.48550/arxiv.2603.07950","title":"Decomposition-Driven Multi-Table Retrieval and Reasoning for Numerical Question Answering","display_name":"Decomposition-Driven Multi-Table Retrieval and Reasoning for Numerical Question Answering","publication_year":2026,"publication_date":"2026-03-09","ids":{"openalex":"https://openalex.org/W7134820642","doi":"https://doi.org/10.48550/arxiv.2603.07950"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.07950","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128676958","display_name":"Feng Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Luo, Feng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121509261","display_name":"Hai Lan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lan, Hai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128665295","display_name":"Hui Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Hui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128649387","display_name":"Zhifeng Bao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bao, Zhifeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128630591","display_name":"Xiaoli Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiaoli","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128690188","display_name":"J. Shane Culpepper","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Culpepper, J. Shane","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5123316658","display_name":"Shazia Sadiq","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sadiq, Shazia","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5128676958"],"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/T10028","display_name":"Topic Modeling","score":0.5138000249862671,"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/T10028","display_name":"Topic Modeling","score":0.5138000249862671,"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":0.1128000020980835,"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"}},{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.0658000037074089,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.8366000056266785},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.753600001335144},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5177000164985657},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47350001335144043},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4675000011920929},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3926999866962433}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.8366000056266785},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7878000140190125},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.753600001335144},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6427000164985657},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5177000164985657},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47350001335144043},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4675000011920929},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3926999866962433},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.39259999990463257},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3772999942302704},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3750999867916107},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3538999855518341},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3149000108242035},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C88548561","wikidata":"https://www.wikidata.org/wiki/Q347599","display_name":"sort","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2694000005722046}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.07950","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.07950","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.07950","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":"pmh:doi:10.48550/arxiv.2603.07950","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","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":{"In":[0],"this":[1],"paper,":[2],"we":[3,78],"study":[4],"the":[5,119,130,136,156],"problem":[6],"of":[7,65,122,139,180],"numerical":[8],"multi-table":[9],"question":[10,131,137],"answering":[11],"(MTQA)":[12],"over":[13,90],"large-scale":[14,48,91,126],"table":[15,49,60,92,100,183],"collections":[16],"(e.g.,":[17],"online":[18],"data":[19],"repositories).":[20],"This":[21],"task":[22],"is":[23],"essential":[24],"in":[25,182,187],"many":[26],"analytical":[27],"applications.":[28],"Existing":[29],"MTQA":[30,37,89,165,174],"solutions,":[31],"such":[32],"as":[33],"text-to-SQL":[34],"or":[35],"open-domain":[36],"methods,":[38,175],"are":[39],"designed":[40],"for":[41,58,88],"databases":[42],"and":[43,85,113,134,142,154,185],"struggle":[44],"when":[45],"applied":[46],"to":[47,103],"collections.":[50],"The":[51],"key":[52],"limitations":[53],"include:":[54],"(1)":[55,97],"Limited":[56],"support":[57],"complex":[59,105],"relationships;":[61],"(2)":[62,109],"Ineffective":[63],"retrieval":[64,184],"relevant":[66,123],"tables":[67,124],"at":[68],"scale;":[69],"(3)":[70,143],"Inaccurate":[71],"answer":[72,188],"generation.":[73],"To":[74],"overcome":[75],"these":[76],"limitations,":[77],"propose":[79],"DMRAL,":[80],"a":[81,99],"Decomposition-driven":[82],"Multi-table":[83],"Retrieval":[84],"Answering":[86],"framework":[87],"collections,":[93],"which":[94,116,147],"consists":[95],"of:":[96],"constructing":[98],"relationship":[101],"graph":[102],"capture":[104],"relationships":[106],"among":[107],"tables;":[108,141],"Table-Aligned":[110],"Question":[111],"Decomposer":[112],"Coverage-Aware":[114],"Retriever,":[115],"jointly":[117],"enable":[118],"effective":[120],"identification":[121],"from":[125],"corpora":[127],"by":[128,151],"enhancing":[129],"decomposition":[132],"quality":[133],"maximizing":[135],"coverage":[138],"retrieved":[140],"Sub-question":[144],"Guided":[145],"Reasoner,":[146],"produces":[148],"correct":[149],"answers":[150],"progressively":[152],"generating":[153],"refining":[155],"reasoning":[157],"program":[158],"based":[159],"on":[160,163],"sub-questions.":[161],"Experiments":[162],"two":[164],"datasets":[166],"demonstrate":[167],"that":[168],"DMRAL":[169],"significantly":[170],"outperforms":[171],"existing":[172],"state-of-the-art":[173],"with":[176],"an":[177],"average":[178],"improvement":[179],"24%":[181],"55%":[186],"accuracy.":[189]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-03-11T00:00:00"}
