{"id":"https://openalex.org/W7165618256","doi":"https://doi.org/10.48550/arxiv.2606.21685","title":"TACO: Task-Aware Column Description Generation Using LLMs","display_name":"TACO: Task-Aware Column Description Generation Using LLMs","publication_year":2026,"publication_date":"2026-06-19","ids":{"openalex":"https://openalex.org/W7165618256","doi":"https://doi.org/10.48550/arxiv.2606.21685"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.21685","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21685","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.2606.21685","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139186859","display_name":"Ting Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Ting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113047111","display_name":"Rakesh R. Menon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Menon, Rakesh R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101600243","display_name":"Yiru Chen","orcid":"https://orcid.org/0000-0002-4488-6785"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yiru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011102706","display_name":"Zifan Liu","orcid":"https://orcid.org/0000-0001-7948-5124"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100600477","display_name":"Yi Tian","orcid":"https://orcid.org/0000-0002-0831-6275"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139205171","display_name":"Fei Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Fei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139179213","display_name":"Anudeep Chimakurthi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chimakurthi, Anudeep","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139161809","display_name":"Prashanthi Ramamurthy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ramamurthy, Prashanthi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064726544","display_name":"Sunav Choudhary","orcid":"https://orcid.org/0000-0002-7711-487X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choudhary, Sunav","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139161435","display_name":"Kun Qian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian, Kun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139190472","display_name":"Yunyao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yunyao","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/T10028","display_name":"Topic Modeling","score":0.6826000213623047,"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":0.6826000213623047,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.1023000031709671,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.06679999828338623,"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/column","display_name":"Column (typography)","score":0.7037000060081482},{"id":"https://openalex.org/keywords/vagueness","display_name":"Vagueness","score":0.6262000203132629},{"id":"https://openalex.org/keywords/downstream","display_name":"Downstream (manufacturing)","score":0.5590999722480774},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4699999988079071},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.45509999990463257},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4187000095844269},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.4133000075817108}],"concepts":[{"id":"https://openalex.org/C2780551164","wikidata":"https://www.wikidata.org/wiki/Q2306599","display_name":"Column (typography)","level":3,"score":0.7037000060081482},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.691100001335144},{"id":"https://openalex.org/C2776825360","wikidata":"https://www.wikidata.org/wiki/Q1411921","display_name":"Vagueness","level":3,"score":0.6262000203132629},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.5590999722480774},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4699999988079071},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.45509999990463257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4521999955177307},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4519999921321869},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38929998874664307},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.36309999227523804},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C93692415","wikidata":"https://www.wikidata.org/wiki/Q1502030","display_name":"Thematic map","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C173483453","wikidata":"https://www.wikidata.org/wiki/Q1040689","display_name":"Synonym (taxonomy)","level":3,"score":0.271699994802475},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2614000141620636},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.21685","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21685","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.2606.21685","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21685","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":[{"score":0.417986124753952,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generating":[0],"accurate":[1],"and":[2,34,47,99,144,147,165,173,180],"informative":[3],"column":[4,13,66,116,131],"descriptions":[5,140],"(e.g.":[6],"\"membership":[7],"status":[8],"of":[9,22,92],"customers\"":[10],"for":[11,18,114,170],"the":[12],"name":[14],"\"cust_mem\")":[15],"is":[16],"essential":[17],"a":[19,111,123],"wide":[20],"range":[21],"downstream":[23,106,157,191],"NLP":[24],"tasks":[25],"on":[26,75],"tabular":[27],"data,":[28],"including":[29],"NL2SQL,":[30],"table":[31],"question":[32],"answering,":[33],"entity":[35,171],"linking.":[36],"This":[37],"problem":[38],"arises":[39],"in":[40],"enterprises,":[41],"domain":[42],"sciences,":[43],"government":[44],"data":[45],"portals,":[46],"so":[48],"on.":[49],"Despite":[50],"its":[51],"importance,":[52],"most":[53],"real-world":[54],"datasets":[55,169,182],"suffer":[56],"from":[57],"missing":[58],"or":[59,68,89,96,102],"cryptic":[60],"documentation,":[61],"often":[62],"due":[63],"to":[64,196],"abbreviated":[65],"names":[67],"domain-specific":[69],"jargon.":[70],"Existing":[71],"approaches":[72],"largely":[73],"rely":[74],"single-prompt":[76],"large":[77],"language":[78],"models":[79],"(LLMs),":[80],"which":[81,129,136,151],"struggle":[82],"with":[83,142],"three":[84],"key":[85],"issues:":[86],"(i)":[87],"inconsistent":[88],"incorrect":[90],"handling":[91],"abbreviations,":[93],"(ii)":[94],"hallucinated":[95],"incomplete":[97],"descriptions,":[98],"(iii)":[100],"redundancy":[101],"vagueness":[103],"that":[104,184],"hinders":[105],"performance.":[107],"We":[108],"present":[109],"TACO,":[110],"task-aware":[112],"framework":[113],"automatic":[115],"description":[117,134,149],"generation":[118],"using":[119,155],"LLMs.":[120],"TACO":[121,185],"introduces":[122],"three-step":[124],"pipeline:":[125],"(1)":[126],"abbreviation":[127],"expansion,":[128],"standardizes":[130],"names;":[132],"(2)":[133],"generation,":[135],"produces":[137],"initial":[138],"semantic":[139],"enriched":[141],"synonyms":[143],"search-oriented":[145],"keywords;":[146],"(3)":[148],"revision,":[150],"refines":[152],"these":[153],"outputs":[154],"simulated":[156],"tasks.":[158],"In":[159],"addition,":[160],"we":[161],"investigate":[162],"human-in-the-loop":[163],"extensions":[164],"release":[166],"new":[167],"evaluation":[168],"linking":[172],"schema":[174],"enrichment.":[175],"Extensive":[176],"experiments":[177],"across":[178],"public":[179],"proprietary":[181],"show":[183],"consistently":[186],"outperforms":[187],"existing":[188],"methods,":[189],"improving":[190],"task":[192],"performance":[193],"by":[194],"up":[195],"32%.":[197]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}
