{"id":"https://openalex.org/W4396757532","doi":"https://doi.org/10.1145/3589334.3645695","title":"OODREB: Benchmarking State-of-the-Art Methods for Out-Of-Distribution Generalization on Relation Extraction","display_name":"OODREB: Benchmarking State-of-the-Art Methods for Out-Of-Distribution Generalization on Relation Extraction","publication_year":2024,"publication_date":"2024-05-08","ids":{"openalex":"https://openalex.org/W4396757532","doi":"https://doi.org/10.1145/3589334.3645695"},"language":"en","primary_location":{"id":"doi:10.1145/3589334.3645695","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645695","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"type":"conference-paper","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/A5047962856","display_name":"Haotian Chen","orcid":"https://orcid.org/0009-0008-5035-8672"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haotian Chen","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0008-5035-8672","affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030235969","display_name":"Houjing Guo","orcid":"https://orcid.org/0009-0009-2136-5440"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Houjing Guo","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0009-2136-5440","affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103232190","display_name":"Bingsheng Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingsheng Chen","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0008-2479-4913","affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046420009","display_name":"Xiangdong Zhou","orcid":"https://orcid.org/0000-0002-5538-7367"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangdong Zhou","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5538-7367","affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04782355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2294","last_page":"2303"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9969000220298767,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9969000220298767,"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":0.9966999888420105,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.994700014591217,"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/benchmarking","display_name":"Benchmarking","score":0.7979151606559753},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.7228509187698364},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7207434773445129},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6205971240997314},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.4955655336380005},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.4923206567764282},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.48670056462287903},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4530680775642395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3252473771572113},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.28512096405029297},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24784037470817566},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1854485273361206},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.0565829873085022}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7979151606559753},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.7228509187698364},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7207434773445129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6205971240997314},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.4955655336380005},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.4923206567764282},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.48670056462287903},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4530680775642395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3252473771572113},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28512096405029297},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24784037470817566},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1854485273361206},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0565829873085022},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589334.3645695","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645695","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1973674431","https://openalex.org/W2090243146","https://openalex.org/W2750779823","https://openalex.org/W2788403449","https://openalex.org/W2798658180","https://openalex.org/W2798734500","https://openalex.org/W2920807444","https://openalex.org/W2952179106","https://openalex.org/W2963718112","https://openalex.org/W2963777632","https://openalex.org/W2963895422","https://openalex.org/W2997591099","https://openalex.org/W2997746169","https://openalex.org/W3093891978","https://openalex.org/W3104390324","https://openalex.org/W3214607109","https://openalex.org/W4213052788","https://openalex.org/W4213447687","https://openalex.org/W4235427396","https://openalex.org/W4280518705","https://openalex.org/W4385893805","https://openalex.org/W6600131058","https://openalex.org/W6600493712"],"related_works":["https://openalex.org/W2976808399","https://openalex.org/W2609844752","https://openalex.org/W2981341912","https://openalex.org/W4285246823","https://openalex.org/W4226278302","https://openalex.org/W4221160509","https://openalex.org/W2547211086","https://openalex.org/W2538200646","https://openalex.org/W1968988659","https://openalex.org/W2888033806"],"abstract_inverted_index":{"Relation":[0],"extraction":[1,69],"(RE)":[2],"methods":[3,81,104,135,144,169],"have":[4],"achieved":[5],"striking":[6],"performance":[7,109],"when":[8],"training":[9,122],"and":[10,15,44,72,87,93,98,115,124,163,193,203],"test":[11],"data":[12,123],"are":[13,26,174],"independently":[14],"identically":[16],"distributed":[17],"(i.i.d).":[18],"However,":[19],"in":[20,31,62,84,112,180],"real-world":[21,181],"scenarios":[22],"where":[23],"RE":[24,63,80,103,134,143,168],"models":[25,173],"trained":[27],"to":[28,41,57,106,119,146,150,185,188],"acquire":[29],"knowledge":[30],"the":[32,34,42,54,75,120,130,151,190],"wild,":[33],"assumption":[35],"can":[36],"hardly":[37],"be":[38],"satisfied":[39],"due":[40,118,149],"different":[43],"unknown":[45],"testing":[46],"distributions.":[47],"In":[48],"this":[49],"paper,":[50],"we":[51],"serve":[52],"as":[53],"first":[55],"effort":[56],"study":[58],"out-of-distribution":[59,67],"(OOD)":[60],"problems":[61],"by":[64],"constructing":[65],"an":[66],"relation":[68],"benchmark":[70,92],"(OODREB)":[71],"then":[73],"investigating":[74],"abilities":[76],"of":[77,133,137,155],"state-of-the-art":[78],"(SOTA)":[79],"on":[82,110,171],"OODREB":[83,111],"both":[85,113],"i.i.d.":[86,114],"OOD":[88,116,191],"settings.":[89],"Our":[90],"proposed":[91],"analysis":[94],"reveal":[95],"new":[96],"findings":[97],"insights:":[99],"(1)":[100],"Existing":[101],"SOTA":[102,142],"struggle":[105],"achieve":[107],"satisfying":[108],"settings":[117],"complex":[121],"biased":[125],"model":[126],"selection":[127],"method.":[128],"Rethinking":[129],"developing":[131],"protocols":[132],"is":[136],"great":[138],"urgency.":[139],"(2)":[140],"The":[141,158],"fail":[145],"learn":[147],"causality":[148,194],"diverse":[152],"linguistic":[153],"expressions":[154],"causal":[156],"information.":[157],"failure":[159],"limits":[160],"their":[161],"robustness":[162],"generalization":[164,192],"ability;":[165],"(3)":[166],"Current":[167],"based":[170],"language":[172],"far":[175],"away":[176],"from":[177],"being":[178],"deployed":[179],"applications.":[182],"We":[183,199],"appeal":[184],"future":[186],"work":[187],"take":[189],"learning":[195],"ability":[196],"into":[197],"consideration.":[198],"make":[200],"our":[201],"annotation":[202],"code":[204],"publicly":[205],"available":[206],"at":[207],"https://github.com/Hytn/OODREB.":[208]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
