{"id":"https://openalex.org/W4389518797","doi":"https://doi.org/10.18653/v1/2023.emnlp-main.296","title":"Can We Edit Factual Knowledge by In-Context Learning?","display_name":"Can We Edit Factual Knowledge by In-Context Learning?","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4389518797","doi":"https://doi.org/10.18653/v1/2023.emnlp-main.296"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2023.emnlp-main.296","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.emnlp-main.296","pdf_url":"https://aclanthology.org/2023.emnlp-main.296.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2023.emnlp-main.296.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101582577","display_name":"Ce Zheng","orcid":"https://orcid.org/0000-0001-9471-575X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ce Zheng","raw_affiliation_strings":["National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092005330","display_name":"Lei Li","orcid":"https://orcid.org/0009-0009-9491-9547"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Li","raw_affiliation_strings":["National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113750837","display_name":"Qingxiu Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingxiu Dong","raw_affiliation_strings":["National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102618106","display_name":"Yuxuan Fan","orcid":"https://orcid.org/0009-0000-3470-7897"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxuan Fan","raw_affiliation_strings":["National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100667025","display_name":"Zhiyong Wu","orcid":"https://orcid.org/0000-0002-6527-5502"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Wu","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100735418","display_name":"Jingjing Xu","orcid":"https://orcid.org/0000-0003-1082-2262"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjing Xu","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021459300","display_name":"Baobao Chang","orcid":"https://orcid.org/0000-0003-2824-6750"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baobao Chang","raw_affiliation_strings":["National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.4409,"has_fulltext":true,"cited_by_count":45,"citation_normalized_percentile":{"value":0.98590284,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4862","last_page":"4876"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9934999942779541,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9789000153541565,"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/computer-science","display_name":"Computer science","score":0.7610273361206055},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.6712565422058105},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.666009247303009},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.63988196849823},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.49806809425354004},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.46199989318847656},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.415477991104126},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3401148319244385},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1504259705543518},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.1254918873310089},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.106477290391922},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09996411204338074},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07742291688919067},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.06953096389770508}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7610273361206055},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.6712565422058105},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.666009247303009},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.63988196849823},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.49806809425354004},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.46199989318847656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.415477991104126},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3401148319244385},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1504259705543518},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.1254918873310089},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.106477290391922},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09996411204338074},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07742291688919067},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.06953096389770508},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2023.emnlp-main.296","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.emnlp-main.296","pdf_url":"https://aclanthology.org/2023.emnlp-main.296.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2023.emnlp-main.296","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.emnlp-main.296","pdf_url":"https://aclanthology.org/2023.emnlp-main.296.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G655826466","display_name":"\u57fa\u4e8e\u8bed\u8a00\u8ba4\u77e5\u673a\u7406\u7684\u6c49\u8bed\u6846\u67b6\u8bed\u4e49\u8ba1\u7b97\u7814\u7a76","funder_award_id":"61936012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389518797.pdf"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W2899771611","https://openalex.org/W2962881743","https://openalex.org/W2963961878","https://openalex.org/W2970641574","https://openalex.org/W2971307358","https://openalex.org/W2980282514","https://openalex.org/W3100355250","https://openalex.org/W3118781290","https://openalex.org/W3122241445","https://openalex.org/W3152884768","https://openalex.org/W3156470785","https://openalex.org/W3172943453","https://openalex.org/W3173673636","https://openalex.org/W3177813494","https://openalex.org/W3202712981","https://openalex.org/W4206118214","https://openalex.org/W4224051134","https://openalex.org/W4225619898","https://openalex.org/W4226278401","https://openalex.org/W4229005866","https://openalex.org/W4281657280","https://openalex.org/W4282980384","https://openalex.org/W4286897388","https://openalex.org/W4286987939","https://openalex.org/W4287111051","https://openalex.org/W4287891464","https://openalex.org/W4292779060","https://openalex.org/W4304192692","https://openalex.org/W4306313145","https://openalex.org/W4306808680","https://openalex.org/W4309088836","https://openalex.org/W4313483544","https://openalex.org/W4320342824","https://openalex.org/W4322718191","https://openalex.org/W4384918448","https://openalex.org/W4389520370"],"related_works":["https://openalex.org/W4289718052","https://openalex.org/W2164121020","https://openalex.org/W2145559838","https://openalex.org/W3116498279","https://openalex.org/W4287549553","https://openalex.org/W3183027292","https://openalex.org/W2974871044","https://openalex.org/W4310285384","https://openalex.org/W2100349471","https://openalex.org/W2716611950"],"abstract_inverted_index":{"Previous":[0],"studies":[1],"have":[2],"shown":[3],"that":[4,106],"large":[5,51],"language":[6],"models":[7],"(LLMs)":[8],"like":[9,165],"GPTs":[10],"store":[11],"massive":[12],"factual":[13,89],"knowledge":[14,21,28,64,108,145],"in":[15,65],"their":[16],"parameters.":[17],"However,":[18,40],"the":[19,42,154,169],"stored":[20,149],"could":[22],"be":[23],"false":[24],"or":[25,161],"outdated.":[26],"Traditional":[27],"editing":[29,109],"methods":[30,125],"refine":[31],"LLMs":[32],"via":[33],"fine-tuning":[34],"on":[35,77,126,138,147],"texts":[36],"containing":[37],"specific":[38],"knowledge.":[39,90,150],"with":[41,130,159],"increasing":[43],"scales":[44],"of":[45,56,101,163,171],"LLMs,":[46],"these":[47],"gradient-based":[48,124],"approaches":[49],"bring":[50],"computation":[52],"costs.":[53],"The":[54,174],"trend":[55],"model-as-a-service":[57],"also":[58,152],"makes":[59],"it":[60],"impossible":[61],"to":[62,123,156],"modify":[63],"black-box":[66],"LMs.":[67],"Inspired":[68],"by":[69],"in-context":[70,107],"learning":[71],"(ICL),":[72],"a":[73,97,118],"new":[74],"paradigm":[75],"based":[76],"demonstration":[78],"contexts":[79],"without":[80,111],"parameter":[81,115],"updating,":[82,116],"we":[83,95],"explore":[84],"whether":[85],"ICL":[86,102],"can":[87],"edit":[88],"To":[91],"answer":[92],"this":[93],"question,":[94],"give":[96],"comprehensive":[98],"empirical":[99],"study":[100],"strategies.":[103],"Experiments":[104],"show":[105],"(IKE),":[110],"any":[112],"gradient":[113],"and":[114,143],"achieves":[117],"competitive":[119],"success":[120],"rate":[121],"compared":[122],"GPT-J":[127],"(6B)":[128],"but":[129,140],"much":[131],"fewer":[132],"side":[133],"effects,":[134],"including":[135],"less":[136,144],"over-editing":[137],"similar":[139],"unrelated":[141],"facts":[142],"forgetting":[146],"previously":[148],"We":[151],"apply":[153],"method":[155],"larger":[157],"LMs":[158],"tens":[160],"hundreds":[162],"parameters":[164],"OPT-175B,":[166],"which":[167],"shows":[168],"scalability":[170],"our":[172],"method.":[173],"code":[175],"is":[176],"available":[177],"at":[178],"https://github.com/pkunlp-icler/IKE.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}
