{"id":"https://openalex.org/W4285602429","doi":"https://doi.org/10.24963/ijcai.2022/761","title":"Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks","display_name":"Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4285602429","doi":"https://doi.org/10.24963/ijcai.2022/761"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2022/761","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/761","pdf_url":"https://www.ijcai.org/proceedings/2022/0761.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.ijcai.org/proceedings/2022/0761.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043988917","display_name":"Haoyu Dong","orcid":"https://orcid.org/0000-0003-1163-3623"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Haoyu Dong","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058829926","display_name":"Zhoujun Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhoujun Cheng","raw_affiliation_strings":["Shanghai Jiao Tong University","Xi'an Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Xi'an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432149","display_name":"Xinyi He","orcid":"https://orcid.org/0000-0001-8557-0464"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyi He","raw_affiliation_strings":["Xi\u2019an Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi\u2019an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101603009","display_name":"Mengyu Zhou","orcid":"https://orcid.org/0000-0002-0322-7513"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mengyu Zhou","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022095905","display_name":"Anda Zhou","orcid":"https://orcid.org/0009-0007-9707-7272"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Anda Zhou","raw_affiliation_strings":["University of Edinburgh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100403505","display_name":"Fan Zhou","orcid":"https://orcid.org/0000-0002-8038-8150"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Zhou","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346423","display_name":"Ao Liu","orcid":"https://orcid.org/0000-0003-3661-4402"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ao Liu","raw_affiliation_strings":["Tokyo Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006300825","display_name":"Shi Han","orcid":"https://orcid.org/0000-0002-0360-6089"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shi Han","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100331488","display_name":"Dongmei Zhang","orcid":"https://orcid.org/0000-0002-9230-2799"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dongmei Zhang","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5426","last_page":"5435"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9977999925613403,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9789999723434448,"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/table","display_name":"Table (database)","score":0.8234565258026123},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7689828276634216},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5473752021789551},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5208883285522461},{"id":"https://openalex.org/keywords/downstream","display_name":"Downstream (manufacturing)","score":0.4911315143108368},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48701101541519165},{"id":"https://openalex.org/keywords/executor","display_name":"Executor","score":0.47255322337150574},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44864189624786377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42241528630256653},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32568663358688354},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10646337270736694}],"concepts":[{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.8234565258026123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7689828276634216},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5473752021789551},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5208883285522461},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.4911315143108368},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48701101541519165},{"id":"https://openalex.org/C180591056","wikidata":"https://www.wikidata.org/wiki/Q654437","display_name":"Executor","level":2,"score":0.47255322337150574},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44864189624786377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42241528630256653},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32568663358688354},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10646337270736694},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2022/761","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/761","pdf_url":"https://www.ijcai.org/proceedings/2022/0761.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2022/761","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/761","pdf_url":"https://www.ijcai.org/proceedings/2022/0761.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285602429.pdf","grobid_xml":"https://content.openalex.org/works/W4285602429.grobid-xml"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W2048282669","https://openalex.org/W2133564696","https://openalex.org/W2140602286","https://openalex.org/W2290320465","https://openalex.org/W2515741950","https://openalex.org/W2549835527","https://openalex.org/W2604225376","https://openalex.org/W2605717780","https://openalex.org/W2804032941","https://openalex.org/W2810376801","https://openalex.org/W2896457183","https://openalex.org/W2898796029","https://openalex.org/W2913178646","https://openalex.org/W2950784811","https://openalex.org/W2965373594","https://openalex.org/W2972324944","https://openalex.org/W2995580406","https://openalex.org/W2996095251","https://openalex.org/W3003937156","https://openalex.org/W3004210300","https://openalex.org/W3035140194","https://openalex.org/W3035231859","https://openalex.org/W3037082750","https://openalex.org/W3061754956","https://openalex.org/W3088604029","https://openalex.org/W3098903006","https://openalex.org/W3102018700","https://openalex.org/W3102264439","https://openalex.org/W3103667349","https://openalex.org/W3103940211","https://openalex.org/W3105238007","https://openalex.org/W3105966348","https://openalex.org/W3116342879","https://openalex.org/W3117281880","https://openalex.org/W3118485687","https://openalex.org/W3147602080","https://openalex.org/W3153051631","https://openalex.org/W3155299751","https://openalex.org/W3157210774","https://openalex.org/W3157891451","https://openalex.org/W3158303960","https://openalex.org/W3165753548","https://openalex.org/W3166890286","https://openalex.org/W3170721718","https://openalex.org/W3173197792","https://openalex.org/W3174086521","https://openalex.org/W3174679944","https://openalex.org/W3176787957","https://openalex.org/W3182778088","https://openalex.org/W3184222203","https://openalex.org/W3197798882","https://openalex.org/W3199258251","https://openalex.org/W4221163895","https://openalex.org/W4230392236","https://openalex.org/W4286902133","https://openalex.org/W4287119949","https://openalex.org/W4287550997","https://openalex.org/W4287554008","https://openalex.org/W4287659415","https://openalex.org/W4287667694","https://openalex.org/W4288089799","https://openalex.org/W4385245566","https://openalex.org/W4385572953"],"related_works":["https://openalex.org/W3132876088","https://openalex.org/W4237320244","https://openalex.org/W3107299409","https://openalex.org/W3044912482","https://openalex.org/W3015007115","https://openalex.org/W3016598040","https://openalex.org/W2230606172","https://openalex.org/W3036516033","https://openalex.org/W3000107590","https://openalex.org/W1550052142"],"abstract_inverted_index":{"Following":[0],"the":[1,7,54,67],"success":[2],"of":[3,13,56,103],"pre-training":[4,15,74,106],"techniques":[5],"in":[6,70],"natural":[8],"language":[9],"domain,":[10],"a":[11,91,100],"flurry":[12],"table":[14,31,34,40,112],"frameworks":[16],"have":[17,21,48,76],"been":[18,49,77],"proposed":[19],"and":[20,42,79,89,108,114,123],"achieved":[22],"new":[23],"state-of-the-arts":[24],"on":[25,120],"various":[26],"downstream":[27,109],"tasks":[28,110],"such":[29],"as":[30],"question":[32],"answering,":[33],"type":[35],"recognition,":[36],"column":[37],"relation":[38],"classification,":[39],"search,":[41],"formula":[43],"prediction.":[44],"Various":[45],"model":[46,104],"architectures":[47],"explored":[50],"to":[51,64,98],"best":[52],"capture":[53],"characteristics":[55],"(semi-)structured":[57],"tables,":[58,72],"especially":[59],"specially-designed":[60],"attention":[61],"mechanisms.":[62],"Moreover,":[63],"fully":[65],"leverage":[66],"supervision":[68],"signals":[69],"unlabeled":[71],"diverse":[73],"objectives":[75],"designed":[78],"evaluated,":[80],"for":[81,111],"example,":[82],"denoising":[83],"cell":[84],"values,":[85],"predicting":[86],"numerical":[87],"relationships,":[88],"learning":[90],"neural":[92],"SQL":[93],"executor.":[94],"This":[95],"survey":[96],"aims":[97],"provide":[99],"comprehensive":[101],"review":[102],"designs,":[105],"objectives,":[107],"pre-training,":[113],"we":[115],"further":[116],"share":[117],"our":[118],"thoughts":[119],"existing":[121],"challenges":[122],"future":[124],"opportunities.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":11}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
