{"id":"https://openalex.org/W4383340203","doi":"https://doi.org/10.1109/tkde.2023.3292974","title":"Evidence Reasoning and Curriculum Learning for Document-level Relation Extraction","display_name":"Evidence Reasoning and Curriculum Learning for Document-level Relation Extraction","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4383340203","doi":"https://doi.org/10.1109/tkde.2023.3292974"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2023.3292974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2023.3292974","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","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/A5101751771","display_name":"Tianyu Xu","orcid":"https://orcid.org/0000-0003-2049-9016"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyu Xu","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2049-9016","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055672506","display_name":"Jianfeng Qu","orcid":"https://orcid.org/0000-0002-2596-2850"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Qu","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004652254","display_name":"Wen Hua","orcid":"https://orcid.org/0000-0001-5456-7035"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wen Hua","raw_affiliation_strings":["Department of Computing, Hong Kong Polytechnic University, HongKong, China"],"raw_orcid":"https://orcid.org/0000-0001-5456-7035","affiliations":[{"raw_affiliation_string":"Department of Computing, Hong Kong Polytechnic University, HongKong, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065529268","display_name":"Zhixu Li","orcid":"https://orcid.org/0000-0003-2355-288X"},"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":"Zhixu Li","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-2355-288X","affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086062267","display_name":"Jiajie Xu","orcid":"https://orcid.org/0000-0001-8227-8636"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajie Xu","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-8227-8636","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100340373","display_name":"An Liu","orcid":"https://orcid.org/0000-0002-6368-576X"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"An Liu","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6368-576X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070439966","display_name":"Lei Zhao","orcid":"https://orcid.org/0000-0002-5123-9279"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhao","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5123-9279","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011384237","display_name":"Xiaofang Zhou","orcid":"https://orcid.org/0000-0001-6343-1455"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaofang Zhou","raw_affiliation_strings":["Department of Computer Science and Engineering, Hong Kong University of Science and Technology, HongKong, China"],"raw_orcid":"https://orcid.org/0000-0001-6343-1455","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Hong Kong University of Science and Technology, HongKong, China","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9518,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78753388,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9991000294685364,"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":0.9991000294685364,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9979000091552734,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9921000003814697,"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/relationship-extraction","display_name":"Relationship extraction","score":0.736607551574707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6909072399139404},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.6380169987678528},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5961394906044006},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5756532549858093},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5607993006706238},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5510925054550171},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.47615739703178406},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4301314651966095},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.40564602613449097},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.14725685119628906}],"concepts":[{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.736607551574707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6909072399139404},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6380169987678528},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5961394906044006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5756532549858093},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5607993006706238},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5510925054550171},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.47615739703178406},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4301314651966095},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.40564602613449097},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.14725685119628906},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tkde.2023.3292974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2023.3292974","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-128864","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-128864","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1604644367","https://openalex.org/W2296073425","https://openalex.org/W2310425190","https://openalex.org/W2746553466","https://openalex.org/W2759211898","https://openalex.org/W2788798739","https://openalex.org/W2907270291","https://openalex.org/W2951274974","https://openalex.org/W2952179106","https://openalex.org/W2962939608","https://openalex.org/W2963167310","https://openalex.org/W2964022985","https://openalex.org/W2986773982","https://openalex.org/W3010512657","https://openalex.org/W3034623328","https://openalex.org/W3035053871","https://openalex.org/W3093891978","https://openalex.org/W3101327207","https://openalex.org/W3103836967","https://openalex.org/W3104390324","https://openalex.org/W3114962796","https://openalex.org/W3116122129","https://openalex.org/W3142849873","https://openalex.org/W3167136668","https://openalex.org/W3172971995","https://openalex.org/W3173169192","https://openalex.org/W3174628768","https://openalex.org/W3174691662","https://openalex.org/W3188999884","https://openalex.org/W3197369495","https://openalex.org/W3199360105","https://openalex.org/W3204348602","https://openalex.org/W3212766995","https://openalex.org/W4226031465","https://openalex.org/W4285151007","https://openalex.org/W4306317304","https://openalex.org/W4385567091","https://openalex.org/W4385573505","https://openalex.org/W6637967152","https://openalex.org/W6730291935","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6760278398","https://openalex.org/W6760842335","https://openalex.org/W6768134808","https://openalex.org/W6782010522","https://openalex.org/W6786637698"],"related_works":["https://openalex.org/W2368651715","https://openalex.org/W159132833","https://openalex.org/W2753023842","https://openalex.org/W1593420896","https://openalex.org/W2791647956","https://openalex.org/W3081459453","https://openalex.org/W2739910088","https://openalex.org/W3114114934","https://openalex.org/W3082447286","https://openalex.org/W4287682749"],"abstract_inverted_index":{"Document-level":[0],"Relation":[1],"Extraction":[2],"(RE)":[3],"is":[4,78,243],"a":[5,17,34,42,69,113,147,152,176,194,258,290],"promising":[6],"task":[7,77],"aiming":[8],"at":[9,199],"identifying":[10],"relations":[11,184],"of":[12,45,75,83,302,307],"multiple":[13],"entity":[14,173],"pairs":[15],"in":[16,81,104,179,219,227],"document.":[18],"Compared":[19],"with":[20,157,206],"the":[21,48,53,96,101,105,165,169,183,188,200,214,228,241,249,268,276,303],"sentence-level":[22],"counterpart,":[23],"it":[24],"has":[25],"raised":[26],"two":[27,284],"significant":[28],"challenges:":[29],"a)":[30],"In":[31,108,212,239,254],"most":[32],"cases,":[33],"relational":[35,90],"fact":[36],"can":[37,94,265],"be":[38],"adequately":[39],"expressed":[40],"via":[41],"small":[43],"subset":[44],"sentences":[46,64],"from":[47,231],"document,":[49],"namely":[50],"evidence.":[51],"But":[52],"traditional":[54],"method":[55,126,198],"cannot":[56],"model":[57],"such":[58],"strong":[59],"semantic":[60],"correlations":[61],"between":[62],"evidence":[63,144,170],"that":[65,264],"collaborate":[66],"to":[67,100,136,163,235,247,267],"describe":[68],"specific":[70],"relation;":[71],"b)":[72],"The":[73],"data":[74,93,229,270],"this":[76,109],"extremely":[79],"long-tail":[80,189],"terms":[82],"too":[84],"many":[85],"NA":[86,215],"instances":[87],"and":[88,120,203,223,233,237,251,272,288,305],"imbalanced":[89],"types.":[91],"Such":[92],"mislead":[95],"tail":[97,252,277],"prediction":[98],"bias":[99],"head":[102],"categories":[103],"RE":[106,286],"model.":[107],"paper,":[110],"we":[111,141,191,256,298],"present":[112],"novel":[114],"<bold":[115,121,128,132],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[116,122,129,133],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">E</b>":[117],"vidence":[118],"reasoning":[119],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">C</b>":[123],"urriculum":[124],"learning":[125,155,197],"for":[127,171],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">D</b>":[130],"oc":[131],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">RE</b>":[134],"(DRE-EC)":[135],"address":[137,187],"these":[138],"challenges.":[139],"Particularly,":[140],"first":[142],"formulate":[143],"extraction":[145],"as":[146,175],"sequential":[148],"decision":[149],"problem":[150],"through":[151],"crafted":[153],"reinforcement":[154],"mechanism":[156],"an":[158,220],"efficient":[159],"path":[160],"searching":[161],"strategy":[162],"reduce":[164],"action":[166],"space.":[167],"Providing":[168],"each":[172],"pair":[174],"customized-filtered":[177],"document":[178],"advance":[180],"helps":[181],"infer":[182],"better.":[185],"To":[186],"issue,":[190],"further":[192],"develop":[193],"hybrid":[195],"curriculum":[196],"NA-level":[201],"(NC)":[202],"relation-level":[204],"(RC)":[205],"our":[207,308],"customized":[208],"difficulty":[209],"measure":[210],"score.":[211],"NC,":[213],"samples":[216],"are":[217],"scheduled":[218],"easy-to-hard":[221],"scheme":[222,242],"gradually":[224],"added,":[225],"resulting":[226],"distribution":[230,271],"ideal":[232],"balanced":[234],"real":[236],"unbalanced.":[238],"RC,":[240],"switched":[244],"into":[245],"hard-to-easy":[246],"enhance":[248],"hard":[250],"samples.":[253],"addition,":[255],"propose":[257],"new":[259],"Equalization":[260],"adaptive":[261],"Focal":[262],"Loss(EFLoss)":[263],"adjust":[266],"changing":[269],"focus":[273],"more":[274],"on":[275,283],"categories.":[278],"We":[279],"conduct":[280],"various":[281],"experiments":[282],"document-level":[285],"benchmarks":[287],"achieve":[289],"remarkable":[291],"improvement":[292],"over":[293],"previous":[294],"competitive":[295],"baselines.":[296],"Furthermore,":[297],"provide":[299],"detailed":[300],"analyses":[301],"advantages":[304],"effectiveness":[306],"method.":[309]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}