{"id":"https://openalex.org/W7160981103","doi":"https://doi.org/10.48550/arxiv.2605.12292","title":"STRABLE: Benchmarking Tabular Machine Learning with Strings","display_name":"STRABLE: Benchmarking Tabular Machine Learning with Strings","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7160981103","doi":"https://doi.org/10.48550/arxiv.2605.12292"},"language":"en","primary_location":{"id":"pmh:oai:HAL:hal-05622316v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05622316","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2026","raw_type":"Preprints, Working Papers, ..."},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-05622316","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136002416","display_name":"Gioia Blayer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Blayer, Gioia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100678380","display_name":"Myung Jun Kim","orcid":"https://orcid.org/0000-0003-2271-1201"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Myung Jun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102616636","display_name":"Aimee Coelho","orcid":"https://orcid.org/0000-0003-3678-6984"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lefebvre, F\u00e9lix","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136019519","display_name":"Lennart Purucker","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Purucker, Lennart","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120446747","display_name":"Alan Arazi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arazi, Alan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136030857","display_name":"Eilam Shapira","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shapira, Eilam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136021257","display_name":"Roi Reichart","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reichart, Roi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031002895","display_name":"Frank Hutter","orcid":"https://orcid.org/0000-0002-2037-3694"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hutter, Frank","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085618039","display_name":"Marine Le Morvan","orcid":"https://orcid.org/0000-0001-9899-221X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morvan, Marine Le","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036807127","display_name":"David Holzm\u00fcller","orcid":"https://orcid.org/0000-0002-9443-0049"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Holzm\u00fcller, David","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136082940","display_name":"Ga\u00ebl Varoquaux","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Varoquaux, Ga\u00ebl","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":11,"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/T11719","display_name":"Data Quality and Management","score":0.5532000064849854,"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"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.5532000064849854,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.07159999758005142,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.05119999870657921,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.8881999850273132},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6032000184059143},{"id":"https://openalex.org/keywords/string","display_name":"String (physics)","score":0.5879999995231628},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.5314000248908997},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4657000005245209},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.39239999651908875}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8881999850273132},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6906999945640564},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6032000184059143},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6025999784469604},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.5879999995231628},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5831000208854675},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.5314000248908997},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4657000005245209},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.39239999651908875},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2648000121116638},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2599000036716461}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:HAL:hal-05622316v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05622316","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2026","raw_type":"Preprints, Working Papers, ..."},{"id":"doi:10.48550/arxiv.2605.12292","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12292","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:oai:HAL:hal-05622316v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05622316","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2026","raw_type":"Preprints, Working Papers, ..."},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6708057522773743}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Benchmarking":[0],"tabular":[1,80,120,147,161,235],"learning":[2,102,121,210,236],"has":[3],"revealed":[4],"the":[5,11,14,75,84,114,156,222],"benefit":[6],"of":[7,13,35,53,97,119,204],"dedicated":[8,47],"architectures,":[9],"pushing":[10],"state":[12],"art.":[15],"But":[16],"real-world":[17,101],"tables":[18,77,154,205],"often":[19],"contain":[20],"string":[21,166],"entries,":[22],"beyond":[23],"numbers,":[24,65],"and":[25,55,106,132,142],"these":[26,89],"settings":[27],"have":[28],"been":[29],"understudied":[30,242],"due":[31],"to":[32,42,61,145,188,206,214,221],"a":[33,36,68,94,146,201,230],"lack":[34],"solid":[37],"benchmarking":[38,95],"suite.":[39],"They":[40],"lead":[41],"new":[43],"research":[44,233],"questions:":[45],"Are":[46],"learners":[48,162],"needed,":[49],"with":[50,67,104,122,164,190,237],"end-to-end":[51,130],"modeling":[52],"strings":[54,63,105,136],"numbers?":[56],"Or":[57],"does":[58],"it":[59,212],"suffice":[60],"encode":[62],"as":[64,66,211,229],"categorical":[69],"encoding?":[70],"And":[71],"if":[72],"so,":[73],"do":[74],"resulting":[76],"resemble":[78],"numerical":[79],"data,":[81],"calling":[82],"for":[83,232],"same":[85],"learners?":[86],"To":[87],"enable":[88],"studies,":[90],"we":[91,196],"contribute":[92],"STRABLE,":[93],"corpus":[96],"108":[98],"tables,":[99,177],"all":[100],"problems":[103],"numbers":[107],"across":[108,192],"diverse":[109],"application":[110],"fields.":[111],"We":[112,149,225],"run":[113],"first":[115,138],"large-scale":[116],"empirical":[117],"study":[118,207],"strings,":[123,238],"evaluating":[124],"445":[125],"pipelines.":[126],"These":[127],"pipelines":[128],"span":[129],"architectures":[131],"modular":[133],"pipelines,":[134],"where":[135],"are":[137,158,219],"encoded,":[139],"then":[140],"post-processed,":[141],"finally":[143],"passed":[144],"learner.":[148],"find":[150],"that,":[151],"because":[152],"most":[153],"in":[155],"wild":[157],"categorical-dominant,":[159],"advanced":[160],"paired":[163],"simple":[165],"embeddings":[167],"achieve":[168],"good":[169,202],"predictions":[170],"at":[171],"low":[172],"computational":[173],"cost.":[174],"On":[175],"free-text-dominant":[176],"large":[178],"LLM":[179,193],"encoders":[180],"become":[181],"competitive.":[182],"Their":[183],"performance":[184],"also":[185],"appears":[186],"sensitive":[187],"post-processing,":[189],"differences":[191],"families.":[194],"Finally,":[195],"show":[197],"that":[198,218],"STRABLE":[199,228],"is":[200],"set":[203],"\"string":[208],"tabular\"":[209],"leads":[213],"generalizable":[215],"pipeline":[216],"rankings":[217],"close":[220],"oracle":[223],"rankings.":[224],"thus":[226],"establish":[227],"foundation":[231],"on":[234],"an":[239],"important":[240],"yet":[241],"area.":[243]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-14T00:00:00"}