{"id":"https://openalex.org/W4403582550","doi":"https://doi.org/10.1145/3627673.3679722","title":"Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answering","display_name":"Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answering","publication_year":2024,"publication_date":"2024-10-20","ids":{"openalex":"https://openalex.org/W4403582550","doi":"https://doi.org/10.1145/3627673.3679722"},"language":"en","primary_location":{"id":"doi:10.1145/3627673.3679722","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679722","pdf_url":null,"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 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3627673.3679722","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101510748","display_name":"Yucheng Shi","orcid":"https://orcid.org/0000-0002-3306-0865"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yucheng Shi","raw_affiliation_strings":["University of Georgia, Athens, Georgia, USA"],"raw_orcid":"https://orcid.org/0000-0002-3306-0865","affiliations":[{"raw_affiliation_string":"University of Georgia, Athens, Georgia, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043697901","display_name":"Qiaoyu Tan","orcid":"https://orcid.org/0000-0001-8999-968X"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiaoyu Tan","raw_affiliation_strings":["New York University, New York, USA"],"raw_orcid":"https://orcid.org/0000-0001-8999-968X","affiliations":[{"raw_affiliation_string":"New York University, New York, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089884284","display_name":"Xuansheng Wu","orcid":"https://orcid.org/0000-0002-7816-7658"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuansheng Wu","raw_affiliation_strings":["University of Georgia, Athens, Georgia, USA"],"raw_orcid":"https://orcid.org/0000-0002-7816-7658","affiliations":[{"raw_affiliation_string":"University of Georgia, Athens, Georgia, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050530149","display_name":"Shaochen Zhong","orcid":null},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaochen Zhong","raw_affiliation_strings":["Rice University, Houston, Texas, USA"],"raw_orcid":"https://orcid.org/0009-0001-7289-3667","affiliations":[{"raw_affiliation_string":"Rice University, Houston, Texas, USA","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071607114","display_name":"Kaixiong Zhou","orcid":"https://orcid.org/0000-0001-5226-8736"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaixiong Zhou","raw_affiliation_strings":["North Carolina State University, Raleigh, North Carolina, USA"],"raw_orcid":"https://orcid.org/0000-0001-5226-8736","affiliations":[{"raw_affiliation_string":"North Carolina State University, Raleigh, North Carolina, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007489034","display_name":"Ninghao Liu","orcid":"https://orcid.org/0000-0002-9170-2424"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ninghao Liu","raw_affiliation_strings":["University of Georgia, Athens, Georgia, USA"],"raw_orcid":"https://orcid.org/0000-0002-9170-2424","affiliations":[{"raw_affiliation_string":"University of Georgia, Athens, Georgia, USA","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2056","last_page":"2066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9876000285148621,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/question-answering","display_name":"Question answering","score":0.8221791982650757},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8208576440811157},{"id":"https://openalex.org/keywords/hop","display_name":"Hop (telecommunications)","score":0.6444128155708313},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5021512508392334},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4876822233200073},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.44349828362464905},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3512830138206482},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.34277862310409546},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.08313462138175964}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.8221791982650757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8208576440811157},{"id":"https://openalex.org/C25906391","wikidata":"https://www.wikidata.org/wiki/Q1432381","display_name":"Hop (telecommunications)","level":2,"score":0.6444128155708313},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5021512508392334},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4876822233200073},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.44349828362464905},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3512830138206482},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.34277862310409546},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.08313462138175964}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627673.3679722","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679722","pdf_url":null,"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 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3627673.3679722","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679722","pdf_url":null,"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 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1532325895","https://openalex.org/W2080133951","https://openalex.org/W2984305408","https://openalex.org/W4225580830","https://openalex.org/W4389519586","https://openalex.org/W4389520296","https://openalex.org/W4393147020","https://openalex.org/W4396735217","https://openalex.org/W4404783928"],"related_works":["https://openalex.org/W2384605597","https://openalex.org/W2387743295","https://openalex.org/W2117210722","https://openalex.org/W2589759689","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W4288267738","https://openalex.org/W2964413124","https://openalex.org/W4388937922","https://openalex.org/W3113264705"],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"have":[4],"shown":[5],"proficiency":[6],"in":[7,152],"question-answering":[8],"tasks":[9],"but":[10],"often":[11],"struggle":[12],"to":[13,18,39,47,95,113],"integrate":[14,42],"real-time":[15],"knowledge,":[16],"leading":[17],"potentially":[19],"outdated":[20],"or":[21],"inaccurate":[22],"responses.":[23],"This":[24],"problem":[25],"becomes":[26],"even":[27],"more":[28],"challenging":[29],"when":[30],"dealing":[31],"with":[32,156],"multi-hop":[33,63],"questions,":[34],"since":[35],"they":[36],"require":[37],"LLMs":[38,94,148],"update":[40],"and":[41,71,126],"multiple":[43],"knowledge":[44],"pieces":[45],"relevant":[46],"the":[48,52,56,74,90,118,123,128],"questions.":[49],"To":[50],"tackle":[51],"problem,":[53],"we":[54],"propose":[55],"Retrieval-Augmented":[57],"model":[58,76],"Editing":[59],"(RAE)":[60],"framework":[61,108,132],"for":[62,138],"question":[64],"answering.":[65],"RAE":[66],"first":[67],"retrieves":[68],"edited":[69],"facts":[70,98],"then":[72],"refines":[73],"language":[75],"through":[77],"in-context":[78],"learning.":[79],"Specifically,":[80],"our":[81,107],"retrieval":[82,141],"approach,":[83],"based":[84],"on":[85],"mutual":[86],"information":[87,116],"maximization,":[88],"leverages":[89],"reasoning":[91],"abilities":[92],"of":[93],"identify":[96],"chain":[97],"that":[99],"traditional":[100],"similarity-based":[101],"searches":[102],"might":[103],"miss.":[104],"In":[105],"addition,":[106],"includes":[109],"a":[110],"pruning":[111],"strategy":[112],"eliminate":[114],"redundant":[115],"from":[117],"retrieved":[119],"facts,":[120],"which":[121],"enhances":[122],"editing":[124],"accuracy":[125],"mitigates":[127],"hallucination":[129],"problem.":[130],"Our":[131,159],"is":[133,161],"supported":[134],"by":[135],"theoretical":[136],"justification":[137],"its":[139],"fact":[140],"efficacy.":[142],"Finally,":[143],"comprehensive":[144],"evaluation":[145],"across":[146],"various":[147],"validates":[149],"RAE's":[150],"ability":[151],"providing":[153],"accurate":[154],"answers":[155],"updated":[157],"knowledge.":[158],"code":[160],"available":[162],"at:":[163],"https://github.com/sycny/RAE.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
