{"id":"https://openalex.org/W7105649579","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228550","title":"ReNIE: Semantic Retrieval and Negative Instances Augmented Information Extraction","display_name":"ReNIE: Semantic Retrieval and Negative Instances Augmented Information Extraction","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W7105649579","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228550"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":null,"display_name":"Haoran Tu","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Tu","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shuo Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Yang","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jianman Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianman Tan","raw_affiliation_strings":["Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University,School of Computer Science and Cyber Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37987034"],"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":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.917900025844574,"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":0.917900025844574,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.00800000037997961,"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":0.007300000172108412,"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/synonym","display_name":"Synonym (taxonomy)","score":0.661899983882904},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6194999814033508},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.5024999976158142},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.43209999799728394},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4047999978065491},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.32710000872612},{"id":"https://openalex.org/keywords/logical-consequence","display_name":"Logical consequence","score":0.31709998846054077},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.3163999915122986}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7490000128746033},{"id":"https://openalex.org/C173483453","wikidata":"https://www.wikidata.org/wiki/Q1040689","display_name":"Synonym (taxonomy)","level":3,"score":0.661899983882904},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6194999814033508},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5084999799728394},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5024999976158142},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.43209999799728394},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3720000088214874},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C134752490","wikidata":"https://www.wikidata.org/wiki/Q374182","display_name":"Logical consequence","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.3163999915122986},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3122999966144562},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2989000082015991},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2890999913215637},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.2734000086784363},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.26330000162124634},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.48958808183670044,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2087079002","https://openalex.org/W2760505947","https://openalex.org/W2998286882","https://openalex.org/W3122241445","https://openalex.org/W3156636935","https://openalex.org/W3173156538","https://openalex.org/W4221166835","https://openalex.org/W4287855163","https://openalex.org/W4382202688","https://openalex.org/W4385307867","https://openalex.org/W4385571184","https://openalex.org/W4385572217","https://openalex.org/W4389523710","https://openalex.org/W4402670463","https://openalex.org/W4404239715","https://openalex.org/W4404781333"],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"the":[1,14,29,52,67,103,111,118,123,137,142,157,165,181,230],"direct":[2],"application":[3],"of":[4,16,55,184,232],"large":[5],"language":[6],"models":[7],"(LLMs)":[8],"for":[9],"in-context":[10,120],"learning":[11],"(ICL)":[12],"in":[13,234],"field":[15],"information":[17,178],"extraction":[18],"(IE)":[19],"has":[20],"demonstrated":[21],"impressive":[22],"performance.":[23],"However,":[24],"ICL":[25,39,47],"still":[26],"lags":[27],"behind":[28],"supervised":[30],"fine-tuning":[31],"approaches.":[32],"Although":[33],"current":[34],"works":[35],"attempt":[36],"to":[37,40,70,101,115,125,159,179],"apply":[38],"IE":[41,87,186],"tasks,":[42],"they":[43],"primarily":[44],"emphasize":[45],"positive":[46],"demonstrations":[48,109],"without":[49],"fully":[50],"exploiting":[51],"potential":[53,161],"value":[54],"negative":[56,59,84,151,170],"instances.":[57],"Incorporating":[58],"instances":[60,85],"introduces":[61,91],"additional":[62,176],"contextual":[63,177],"variations":[64],"and":[65,83,95,141,213],"enhances":[66],"model\u2019s":[68,104,119,182],"sensitivity":[69],"subtle":[71],"semantic":[72,81,113],"differences.":[73],"In":[74],"this":[75],"paper,":[76],"we":[77,193],"propose":[78],"ReNIE,":[79],"a":[80,96],"retrieval":[82],"augmented":[86],"framework.":[88],"Our":[89],"framework":[90],"Semantic-Level":[92],"Retrieval":[93],"(SLR)":[94],"Robustness":[97],"Enhancement":[98],"Strategy":[99],"(RES)":[100],"enhance":[102,180],"generation":[105],"process.":[106],"SLR":[107],"retrieves":[108],"with":[110,130,153,172],"highest":[112],"similarity":[114],"serve":[116],"as":[117],"prompt,":[121],"guiding":[122,156],"model":[124,158],"generate":[126],"predictions":[127],"that":[128,223],"align":[129],"task":[131],"characteristics.":[132],"RES":[133],"comprises":[134],"two":[135],"components:":[136],"boundary":[138,147,154],"disturbance":[139,148],"method":[140,149,168,225],"synonym":[143,166,173],"perturbation":[144,167],"method.":[145],"The":[146],"generates":[150],"samples":[152,171],"errors,":[155],"avoid":[160],"boundary-related":[162],"mistakes,":[163],"while":[164],"creates":[169],"variations,":[174],"providing":[175],"understanding":[183],"predefined":[185],"categories.":[187],"To":[188],"validate":[189],"our":[190,224],"proposed":[191],"method,":[192],"conduct":[194],"experiments":[195],"on":[196],"13":[197],"Named":[198],"Entity":[199],"Recognition":[200],"(NER)":[201],"datasets,":[202,207,212],"2":[203,208],"Relation":[204],"Extraction":[205,210,217],"(RE)":[206],"Event":[209,215],"(EE)":[211],"3":[214],"Argument":[216],"(EAE)":[218],"datasets.":[219],"Experimental":[220],"results":[221],"demonstrate":[222],"achieves":[226],"comparable":[227],"performance":[228],"across":[229],"majority":[231],"datasets":[233],"unseen":[235],"domains.":[236]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-11-14T00:00:00"}