{"id":"https://openalex.org/W4384895516","doi":"https://doi.org/10.1145/3539618.3592052","title":"Retrieval-Enhanced Generative Model for Large-Scale Knowledge Graph Completion","display_name":"Retrieval-Enhanced Generative Model for Large-Scale Knowledge Graph Completion","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4384895516","doi":"https://doi.org/10.1145/3539618.3592052"},"language":"en","primary_location":{"id":"doi:10.1145/3539618.3592052","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3539618.3592052","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3539618.3592052","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 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3539618.3592052","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102920370","display_name":"Donghan Yu","orcid":"https://orcid.org/0009-0004-0649-1338"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Donghan Yu","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0009-0004-0649-1338","affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101421478","display_name":"Yiming Yang","orcid":"https://orcid.org/0000-0001-8322-607X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiming Yang","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0000-0001-8322-607X","affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102920370"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":1.6949,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.87241155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2334","last_page":"2338"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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/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/T11719","display_name":"Data Quality and Management","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.8045759797096252},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7886814475059509},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7855408191680908},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7382985353469849},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5914863348007202},{"id":"https://openalex.org/keywords/memorization","display_name":"Memorization","score":0.5785506963729858},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5730996131896973},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5375857353210449},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.507188081741333},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4966748356819153},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4745693504810333},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4680618345737457},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.45827651023864746},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36188653111457825},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32358986139297485},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3231082558631897},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.13146084547042847},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07982593774795532}],"concepts":[{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.8045759797096252},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7886814475059509},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7855408191680908},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7382985353469849},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5914863348007202},{"id":"https://openalex.org/C30038468","wikidata":"https://www.wikidata.org/wiki/Q4354775","display_name":"Memorization","level":2,"score":0.5785506963729858},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5730996131896973},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5375857353210449},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.507188081741333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4966748356819153},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4745693504810333},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4680618345737457},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45827651023864746},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36188653111457825},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32358986139297485},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3231082558631897},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.13146084547042847},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07982593774795532},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3539618.3592052","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3539618.3592052","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3539618.3592052","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 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3539618.3592052","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3539618.3592052","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3539618.3592052","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 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384895516.pdf","grobid_xml":"https://content.openalex.org/works/W4384895516.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W2080133951","https://openalex.org/W2094728533","https://openalex.org/W2250184916","https://openalex.org/W2728059831","https://openalex.org/W2747329762","https://openalex.org/W2799037506","https://openalex.org/W2912516411","https://openalex.org/W2963157366","https://openalex.org/W3090656107","https://openalex.org/W3099403815","https://openalex.org/W3099700870","https://openalex.org/W3102654612","https://openalex.org/W3151929433","https://openalex.org/W3156789018","https://openalex.org/W4210690412","https://openalex.org/W4225412853","https://openalex.org/W4252076394","https://openalex.org/W6600001191","https://openalex.org/W6600755281","https://openalex.org/W6602127427","https://openalex.org/W6602311867","https://openalex.org/W6606805609","https://openalex.org/W6610116125","https://openalex.org/W6727875242"],"related_works":["https://openalex.org/W4387561393","https://openalex.org/W3163481960","https://openalex.org/W3093895509","https://openalex.org/W4283526844","https://openalex.org/W280704926","https://openalex.org/W2476068070","https://openalex.org/W4323971310","https://openalex.org/W2893372175","https://openalex.org/W2323394100","https://openalex.org/W1972827106"],"abstract_inverted_index":{"The":[0],"task":[1],"of":[2,8,62,80],"knowledge":[3,18],"graph":[4],"completion":[5],"(KGC)":[6],"is":[7],"great":[9],"importance.":[10],"To":[11,82],"achieve":[12],"scalability":[13],"when":[14],"dealing":[15],"with":[16,46,111],"large-scale":[17],"graphs,":[19],"recent":[20],"works":[21],"formulate":[22],"KGC":[23,92],"as":[24,41,105],"a":[25,77,89],"sequence-to-sequence":[26],"process,":[27],"where":[28],"the":[29,34,52,60,67,70,73,100],"incomplete":[30],"triplet":[31],"(input)":[32],"and":[33,58,102,124,130],"missing":[35],"entity":[36],"(output)":[37],"are":[38],"both":[39],"verbalized":[40],"text":[42],"sequences.":[43],"However,":[44],"inference":[45],"these":[47],"methods":[48],"relies":[49],"solely":[50],"on":[51,120],"model":[53,71],"parameters":[54],"for":[55],"implicit":[56],"reasoning":[57],"neglects":[59],"use":[61],"KG":[63,101],"itself,":[64],"which":[65,94,126],"limits":[66],"performance":[68,119],"since":[69],"lacks":[72],"capacity":[74],"to":[75,107],"memorize":[76],"vast":[78],"number":[79],"triplets.":[81],"tackle":[83],"this":[84],"issue,":[85],"we":[86],"introduce":[87],"ReSKGC,":[88],"Retrieval-enhanced":[90],"Seq2seq":[91],"model,":[93],"selects":[95],"semantically":[96],"relevant":[97],"triplets":[98],"from":[99],"uses":[103],"them":[104],"evidence":[106],"guide":[108],"output":[109],"generation":[110],"explicit":[112],"reasoning.":[113],"Our":[114],"method":[115],"has":[116],"demonstrated":[117],"state-of-the-art":[118],"benchmark":[121],"datasets":[122],"Wikidata5M":[123],"WikiKG90Mv2,":[125],"contain":[127],"about":[128],"5M":[129],"90M":[131],"entities,":[132],"respectively.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3}],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}
