{"id":"https://openalex.org/W4415707677","doi":"https://doi.org/10.1109/icme59968.2025.11209132","title":"ReFEdit: Rehearsal-Free Lifelong Knowledge Editing for Large Language Models","display_name":"ReFEdit: Rehearsal-Free Lifelong Knowledge Editing for Large Language Models","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415707677","doi":"https://doi.org/10.1109/icme59968.2025.11209132"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209132","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209132","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5101087836","display_name":"Xianjie Mo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianjie Mo","raw_affiliation_strings":["Pengcheng Laboratory,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pengcheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004433495","display_name":"Youcheng Pan","orcid":"https://orcid.org/0000-0002-8270-5455"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youcheng Pan","raw_affiliation_strings":["Pengcheng Laboratory,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pengcheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027262293","display_name":"Yongshuai Hou","orcid":"https://orcid.org/0000-0001-6994-8295"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongshuai Hou","raw_affiliation_strings":["Pengcheng Laboratory,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pengcheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100752685","display_name":"Ping Luo","orcid":"https://orcid.org/0000-0002-6645-4721"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Luo","raw_affiliation_strings":["Pengcheng Laboratory,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pengcheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101632572","display_name":"Yang Xiang","orcid":"https://orcid.org/0000-0003-1395-6805"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Xiang","raw_affiliation_strings":["Pengcheng Laboratory,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pengcheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14858513,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.3598000109195709,"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":0.3598000109195709,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.19140000641345978,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.11949999630451202,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5863000154495239},{"id":"https://openalex.org/keywords/orthogonality","display_name":"Orthogonality","score":0.5288000106811523},{"id":"https://openalex.org/keywords/lifelong-learning","display_name":"Lifelong learning","score":0.41600000858306885},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4156999886035919},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4043999910354614},{"id":"https://openalex.org/keywords/knowledge-based-systems","display_name":"Knowledge-based systems","score":0.3488999903202057},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.34200000762939453},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.34040001034736633}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7997999787330627},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5863000154495239},{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.5288000106811523},{"id":"https://openalex.org/C108771440","wikidata":"https://www.wikidata.org/wiki/Q368475","display_name":"Lifelong learning","level":2,"score":0.41600000858306885},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4043999910354614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3725999891757965},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3262999951839447},{"id":"https://openalex.org/C2780589192","wikidata":"https://www.wikidata.org/wiki/Q7285140","display_name":"Raising (metalworking)","level":2,"score":0.326200008392334},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C2780967703","wikidata":"https://www.wikidata.org/wiki/Q2571389","display_name":"Collaborative editing","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C56289545","wikidata":"https://www.wikidata.org/wiki/Q6423376","display_name":"Knowledge integration","level":3,"score":0.29190000891685486},{"id":"https://openalex.org/C84685590","wikidata":"https://www.wikidata.org/wiki/Q1540472","display_name":"Knowledge engineering","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C124469403","wikidata":"https://www.wikidata.org/wiki/Q1813993","display_name":"Procedural knowledge","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209132","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209132","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2251939518","https://openalex.org/W2923014074","https://openalex.org/W2962881743","https://openalex.org/W2963846996","https://openalex.org/W2970476646","https://openalex.org/W2978670439","https://openalex.org/W3102659883","https://openalex.org/W4205460703","https://openalex.org/W4206118214","https://openalex.org/W4253067820","https://openalex.org/W4389518797","https://openalex.org/W4393147125","https://openalex.org/W4393152647","https://openalex.org/W4404782583","https://openalex.org/W4404782881","https://openalex.org/W4412945029"],"related_works":[],"abstract_inverted_index":{"Knowledge":[0,91],"editing":[1,47,156],"has":[2],"emerged":[3],"as":[4,63],"a":[5,52,65,88,167],"promising":[6],"strategy":[7],"for":[8,32,162],"updating":[9],"obsolete":[10],"or":[11],"inaccurate":[12],"knowledge":[13,33,46,72,122,155,176],"embedded":[14],"within":[15],"large":[16],"language":[17],"models":[18],"(LLMs)":[19],"without":[20],"costly":[21],"fine-tuning.":[22],"The":[23],"widely":[24],"adopted":[25],"locating-then-editing":[26],"paradigm":[27],"first":[28],"locates":[29],"parameters":[30],"responsible":[31],"storage":[34],"and":[35,79,112,145,173],"then":[36],"modifies":[37],"them":[38],"to":[39,73,108],"integrate":[40],"updated":[41],"knowledge.":[42],"However,":[43],"in":[44],"lifelong":[45,175],"scenarios,":[48],"catastrophic":[49,134],"forgetting":[50],"poses":[51],"significant":[53],"challenge.":[54],"Existing":[55],"methods":[56,157],"often":[57],"rely":[58],"on":[59,99,127,138],"rehearsal-based":[60,154],"techniques,":[61],"such":[62],"storing":[64],"feature":[66],"covariance":[67],"matrix":[68],"of":[69],"previously":[70,128],"preserved":[71,129],"constrain":[74],"errors,":[75],"thus":[76],"raising":[77],"efficiency":[78],"privacy":[80],"issues.":[81],"To":[82],"address":[83],"this,":[84],"we":[85],"introduce":[86],"ReFEdit,":[87],"Rehearsal-Free":[89],"Lifelong":[90],"Editing":[92],"framework":[93],"that":[94,148],"enforces":[95],"an":[96],"orthogonality":[97],"restriction":[98],"parameter":[100],"modifications.":[101],"By":[102],"aligning":[103],"the":[104,110,117,125,160,163],"update":[105],"direction":[106],"orthogonally":[107],"both":[109],"latest":[111],"initial":[113],"parameters,":[114],"ReFEdit":[115,149],"minimizes":[116],"interference":[118],"between":[119],"sequentially":[120],"edited":[121],"while":[123,158],"mitigating":[124],"impact":[126],"knowledge,":[130],"thereby":[131],"effectively":[132],"addressing":[133],"forgetting.":[135],"Extensive":[136],"evaluations":[137],"multiple":[139],"representative":[140],"LLMs,":[141],"including":[142],"LLaMA3,":[143],"GPT-J,":[144],"GPT2-XL,":[146],"demonstrate":[147],"significantly":[150],"outperforms":[151],"most":[152],"existing":[153],"eliminating":[159],"need":[161],"rehearsal":[164],"phase,":[165],"marking":[166],"substantial":[168],"advancement":[169],"toward":[170],"more":[171],"reliable":[172],"flexible":[174],"editing.":[177],"Our":[178],"code":[179],"is":[180],"available":[181],"at:":[182],"https://github.com/Cedric-Mo/ReFEdit":[183]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-30T00:00:00"}
