{"id":"https://openalex.org/W7131372002","doi":"https://doi.org/10.1109/ccwc67433.2026.11393867","title":"VersaTable: Generating Realistic Mixed-Type Tables Blending Categorical Tags, Variable-Length Lists, and Free Text","display_name":"VersaTable: Generating Realistic Mixed-Type Tables Blending Categorical Tags, Variable-Length Lists, and Free Text","publication_year":2026,"publication_date":"2026-01-05","ids":{"openalex":"https://openalex.org/W7131372002","doi":"https://doi.org/10.1109/ccwc67433.2026.11393867"},"language":"en","primary_location":{"id":"doi:10.1109/ccwc67433.2026.11393867","doi":"https://doi.org/10.1109/ccwc67433.2026.11393867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc67433.2026.11393867","pdf_url":null,"source":{"id":"https://openalex.org/S4363608098","display_name":"IEEE Annual Computing and Communication Workshop and Conference (CCWC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 16th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088972922","display_name":"Mark Bilinski","orcid":"https://orcid.org/0000-0003-3635-2027","observed_orcids":["https://orcid.org/0000-0003-3635-2027"]},"institutions":[{"id":"https://openalex.org/I1339224429","display_name":"Naval Information Warfare Center Pacific","ror":"https://ror.org/01gs1cg95","country_code":"US","type":"government","lineage":["https://openalex.org/I1330347796","https://openalex.org/I1339224429","https://openalex.org/I2802223155","https://openalex.org/I3130687028"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark Bilinski","raw_affiliation_strings":["NIWC Pacific,San Diego,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NIWC Pacific,San Diego,USA","institution_ids":["https://openalex.org/I1339224429"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008430584","display_name":"Ryan Gabrys","orcid":"https://orcid.org/0000-0002-9197-3371","observed_orcids":["https://orcid.org/0000-0002-9197-3371"]},"institutions":[{"id":"https://openalex.org/I1339224429","display_name":"Naval Information Warfare Center Pacific","ror":"https://ror.org/01gs1cg95","country_code":"US","type":"government","lineage":["https://openalex.org/I1330347796","https://openalex.org/I1339224429","https://openalex.org/I2802223155","https://openalex.org/I3130687028"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ryan Gabrys","raw_affiliation_strings":["NIWC Pacific,San Diego,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NIWC Pacific,San Diego,USA","institution_ids":["https://openalex.org/I1339224429"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034290177","display_name":"Daniel Silva","orcid":"https://orcid.org/0000-0001-7973-5226","observed_orcids":["https://orcid.org/0000-0001-7973-5226"]},"institutions":[{"id":"https://openalex.org/I1339224429","display_name":"Naval Information Warfare Center Pacific","ror":"https://ror.org/01gs1cg95","country_code":"US","type":"government","lineage":["https://openalex.org/I1330347796","https://openalex.org/I1339224429","https://openalex.org/I2802223155","https://openalex.org/I3130687028"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Silva","raw_affiliation_strings":["NIWC Pacific,San Diego,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NIWC Pacific,San Diego,USA","institution_ids":["https://openalex.org/I1339224429"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1339224429"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1486","last_page":"1493"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.2957000136375427,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.2957000136375427,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.1940000057220459,"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/T10028","display_name":"Topic Modeling","score":0.149399995803833,"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/nested-tables","display_name":"nested tables","score":0.6309999823570251},{"id":"https://openalex.org/keywords/unstructured-text","display_name":"unstructured text","score":0.5360000133514404},{"id":"https://openalex.org/keywords/tabular-data-generation","display_name":"tabular data generation","score":0.7649999856948853},{"id":"https://openalex.org/keywords/two-stage-pipeline","display_name":"two-stage pipeline","score":0.5070000290870667}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.770799994468689},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7160000205039978},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6822999715805054},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5975000262260437},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.5751000046730042},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4706999957561493},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4674000144004822},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3758000135421753},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.31439998745918274},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.2743000090122223}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccwc67433.2026.11393867","doi":"https://doi.org/10.1109/ccwc67433.2026.11393867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc67433.2026.11393867","pdf_url":null,"source":{"id":"https://openalex.org/S4363608098","display_name":"IEEE Annual Computing and Communication Workshop and Conference (CCWC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 16th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2295598076","https://openalex.org/W2626778328","https://openalex.org/W2806276686","https://openalex.org/W2995327724","https://openalex.org/W3174086521","https://openalex.org/W4389524441","https://openalex.org/W4407832462"],"related_works":["https://openalex.org/W4393119099","https://openalex.org/W7208754441","https://openalex.org/W7131814777","https://openalex.org/W4401666241","https://openalex.org/W6884304853","https://openalex.org/W4411120575","https://openalex.org/W4385565070","https://openalex.org/W7083589243","https://openalex.org/W4409243237","https://openalex.org/W4366462187"],"abstract_inverted_index":{"Many":[0],"cyber-defense,":[1],"healthcare,":[2],"finance":[3],"and":[4,20,29,70,78,95],"retail":[5],"tasks":[6],"have":[7],"a":[8,49,62,66,86],"need":[9],"for":[10,92],"realistic":[11],"mixed-type":[12],"tables":[13],"that":[14,52],"blend":[15],"categorical":[16],"tags,":[17],"variable-length":[18],"lists":[19],"free":[21],"text.":[22],"Existing":[23],"techniques":[24],"often":[25,38],"flatten":[26],"these":[27],"structures,":[28],"recent":[30],"LLM-based":[31],"approaches":[32],"capture":[33],"semantics":[34],"but":[35],"their":[36],"performance":[37],"drops":[39],"in":[40],"the":[41],"presence":[42],"of":[43],"nested":[44],"fields.":[45],"We":[46],"present":[47],"VersaTable,":[48],"two-stage":[50],"pipeline":[51],"first":[53],"captures":[54],"compact":[55],"attributes,":[56],"then":[57],"fills":[58],"long-text":[59],"banners":[60],"with":[61],"lightweight":[63],"specialist.":[64],"On":[65],"large":[67],"Host-Config":[68],"corpus":[69],"five":[71],"public":[72],"benchmarks,":[73],"VersaTable":[74],"raises":[75],"likelihood,":[76],"coverage":[77],"discriminator":[79],"accuracy":[80],"over":[81],"strong":[82],"baselines,":[83],"making":[84],"it":[85],"potential":[87],"tabular":[88],"data":[89],"generation":[90],"method":[91],"both":[93],"security":[94],"non-security":[96],"domains.":[97]},"counts_by_year":[],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-02-26T00:00:00"}