{"id":"https://openalex.org/W7160335161","doi":"https://doi.org/10.48550/arxiv.2605.01018","title":"WildTableBench: Benchmarking Multimodal Foundation Models on Table Understanding In the Wild","display_name":"WildTableBench: Benchmarking Multimodal Foundation Models on Table Understanding In the Wild","publication_year":2026,"publication_date":"2026-05-01","ids":{"openalex":"https://openalex.org/W7160335161","doi":"https://doi.org/10.48550/arxiv.2605.01018"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.01018","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01018","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.2605.01018","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135372916","display_name":"Junzhe Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Junzhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135354508","display_name":"Xiaoxiao Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Xiaoxiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135417131","display_name":"Yan Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134906338","display_name":"Yuxuan Hou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hou, Yuxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121383465","display_name":"Ruotian Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Ruotian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135344164","display_name":"Sirui Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Sirui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135283842","display_name":"Hehe Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Hehe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135325889","display_name":"Serena Yeung-Levy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yeung-Levy, Serena","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135303834","display_name":"Xin S. Yu","orcid":"https://orcid.org/0000-0003-0322-6833"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Xin","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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.30869999527931213,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.30869999527931213,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.040300000458955765,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.03840000182390213,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/table","display_name":"Table (database)","score":0.8195000290870667},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.7843999862670898},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6801000237464905},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.5406000018119812},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.504800021648407},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4075999855995178},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.38989999890327454}],"concepts":[{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.8195000290870667},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7843999862670898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.682200014591217},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6801000237464905},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.5406000018119812},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.504800021648407},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45719999074935913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.454800009727478},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3946000039577484},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3919999897480011},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.38989999890327454},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C63882131","wikidata":"https://www.wikidata.org/wiki/Q17122954","display_name":"Strengths and weaknesses","level":2,"score":0.3734000027179718},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.30250000953674316},{"id":"https://openalex.org/C68476402","wikidata":"https://www.wikidata.org/wiki/Q1456936","display_name":"Table of contents","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.26499998569488525}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.01018","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01018","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.2605.01018","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01018","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":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4800904095172882}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Using":[0],"multimodal":[1,113],"foundation":[2,114],"models":[3,115,128],"to":[4,132,139],"analyze":[5],"table":[6,39,72,81,172],"images":[7,40,43,73,82],"is":[8],"a":[9,167],"high-value":[10],"yet":[11],"challenging":[12],"application":[13],"in":[14,147],"consumer":[15],"and":[16,47,55,87,97,111,143,150,154,163],"enterprise":[17],"scenarios.":[18],"Despite":[19],"its":[20],"importance,":[21],"current":[22,160],"evaluations":[23],"rely":[24],"largely":[25],"on":[26,116],"structured-text":[27],"tables":[28],"or":[29],"clean":[30],"rendered":[31],"images,":[32],"leaving":[33],"the":[34,65],"visual":[35],"complexity":[36],"of":[37],"in-the-wild":[38],"underexplored.":[41],"Such":[42],"feature":[44],"varied":[45],"layouts":[46],"diverse":[48,90],"domains":[49],"that":[50],"demand":[51],"sophisticated":[52],"structural":[53,148],"perception":[54,149],"numerical":[56],"reasoning.":[57,151],"To":[58],"bridge":[59],"this":[60,117],"gap,":[61],"we":[62],"introduce":[63],"WildTableBench,":[64],"first":[66],"question-answering":[67],"benchmark":[68,170],"for":[69,171],"naturally":[70],"occurring":[71],"from":[74,84,130],"real-world":[75],"settings.":[76],"WildTableBench":[77,165],"comprises":[78],"402":[79],"high-information-density":[80],"collected":[83],"online":[85],"forums":[86],"websites":[88],"across":[89,103],"domains,":[91],"together":[92],"with":[93],"928":[94],"manually":[95],"annotated":[96],"verified":[98],"questions":[99],"spanning":[100],"17":[101],"subtypes":[102],"five":[104],"categories.":[105],"We":[106,134],"evaluate":[107],"21":[108],"frontier":[109],"proprietary":[110],"open-source":[112],"benchmark.":[118],"Only":[119],"one":[120],"model":[121,141,161],"exceeds":[122],"50%":[123],"accuracy,":[124],"while":[125],"all":[126],"remaining":[127],"range":[129],"4.1%":[131],"49.9%.":[133],"further":[135],"conduct":[136],"diagnostic":[137,169],"analyses":[138,155],"characterize":[140],"failures":[142],"reveal":[144],"persistent":[145],"weaknesses":[146],"These":[152],"results":[153],"provide":[156],"useful":[157],"insights":[158],"into":[159],"capabilities":[162],"establish":[164],"as":[166],"valuable":[168],"image":[173],"understanding.":[174],"Dataset:":[175],"https://huggingface.co/datasets/jzhuang/WildTableBench":[176],"Code:":[177],"https://github.com/hjzhe/WildTableBench":[178],"Leaderboard:":[179],"https://hjzhe.github.io/WildTableBench":[180]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-06T00:00:00"}
