{"id":"https://openalex.org/W4416034115","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.892","title":"DrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains","display_name":"DrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416034115","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.892"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.892","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.892","pdf_url":"https://aclanthology.org/2025.findings-emnlp.892.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-emnlp.892.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034370661","display_name":"Yongkang Xiao","orcid":"https://orcid.org/0000-0002-8808-8371"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yongkang Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Sinian Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sinian Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087376557","display_name":"Yiping Dai","orcid":"https://orcid.org/0000-0002-1144-6521"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Dai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102592693","display_name":"Huixue Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huixue Zhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102749628","display_name":"Jue Hou","orcid":"https://orcid.org/0000-0002-8441-8468"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jue Hou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028035987","display_name":"Jie Ding","orcid":"https://orcid.org/0000-0001-9927-5415"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jie Ding","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100422102","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0002-8729-8393"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5175,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.93679791,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"16432","last_page":"16445"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9541000127792358,"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":0.9541000127792358,"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":0.01360000018030405,"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":0.010400000028312206,"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/graph","display_name":"Graph","score":0.44350001215934753},{"id":"https://openalex.org/keywords/knowledge-representation-and-reasoning","display_name":"Knowledge representation and reasoning","score":0.2824999988079071},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.2797999978065491},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.26579999923706055},{"id":"https://openalex.org/keywords/knowledge-based-systems","display_name":"Knowledge-based systems","score":0.26080000400543213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5612999796867371},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3982999920845032},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3269999921321869},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.23659999668598175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-emnlp.892","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.892","pdf_url":"https://aclanthology.org/2025.findings-emnlp.892.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.892","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.892","pdf_url":"https://aclanthology.org/2025.findings-emnlp.892.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1729030118","display_name":null,"funder_award_id":"R01AG078154","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G2234864871","display_name":null,"funder_award_id":"R01AT009457","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G2545608675","display_name":null,"funder_award_id":"1R21MD019134-01","funder_id":"https://openalex.org/F4320337534","funder_display_name":"National Institute on Minority Health and Health Disparities"},{"id":"https://openalex.org/G7249977270","display_name":null,"funder_award_id":"R01DK115629","funder_id":"https://openalex.org/F4320337357","funder_display_name":"National Institute of Diabetes and Digestive and Kidney Diseases"},{"id":"https://openalex.org/G7374104320","display_name":null,"funder_award_id":"1R21MD019134","funder_id":"https://openalex.org/F4320337534","funder_display_name":"National Institute on Minority Health and Health Disparities"},{"id":"https://openalex.org/G8567306661","display_name":null,"funder_award_id":"R01CA287413","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"},{"id":"https://openalex.org/F4320337357","display_name":"National Institute of Diabetes and Digestive and Kidney Diseases","ror":"https://ror.org/00adh9b73"},{"id":"https://openalex.org/F4320337534","display_name":"National Institute on Minority Health and Health Disparities","ror":"https://ror.org/0493hgw16"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416034115.pdf","grobid_xml":"https://content.openalex.org/works/W4416034115.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Knowledge":[0,68],"graph":[1,30,36,55,93,109],"completion":[2],"(KGC)":[3],"aims":[4],"to":[5,43,78,96,118],"predict":[6],"missing":[7],"triples":[8,16],"in":[9,38,155],"knowledge":[10],"graphs":[11],"(KGs)":[12],"by":[13,104],"leveraging":[14],"existing":[15],"and":[17,52,82,141,162],"textual":[18,39],"information.Recently,":[19],"generative":[20],"large":[21],"language":[22],"models":[23],"(LLMs)":[24],"have":[25],"been":[26],"increasingly":[27],"employed":[28],"for":[29,50,67,100,130],"tasks.However,":[31],"current":[32],"approaches":[33],"typically":[34],"encode":[35],"context":[37],"form,":[40],"which":[41,123],"fails":[42],"fully":[44],"exploit":[45],"the":[46,86,105,115,120,128,146,156],"potential":[47],"of":[48,149],"LLMs":[49,66],"perceiving":[51],"reasoning":[53],"about":[54],"structures.To":[56],"address":[57],"this":[58],"limitation,":[59],"we":[60],"propose":[61],"DrKGC":[62],"(Dynamic":[63],"Subgraph":[64],"Retrieval-Augmented":[65],"Graph":[69],"Completion).DrKGC":[70],"employs":[71],"a":[72,90,98,108,151],"flexible":[73],"lightweight":[74],"model":[75],"training":[76],"strategy":[77],"learn":[79],"structural":[80,121],"embeddings":[81],"logical":[83],"rules":[84],"within":[85],"KG.It":[87],"then":[88,125],"leverages":[89],"novel":[91],"bottom-up":[92],"retrieval":[94],"method":[95],"extract":[97],"subgraph":[99,117],"each":[101],"query":[102],"guided":[103],"learned":[106],"rules.Finally,":[107],"convolutional":[110],"network":[111],"(GCN)":[112],"adapter":[113],"uses":[114],"retrieved":[116],"enhance":[119],"embeddings,":[122],"are":[124],"integrated":[126],"into":[127],"prompt":[129],"effective":[131],"LLM":[132],"finetuning.Experimental":[133],"results":[134],"on":[135],"two":[136,142],"general":[137],"domain":[138,158],"benchmark":[139],"datasets":[140,144],"biomedical":[143,157],"demonstrate":[145],"superior":[147],"performance":[148],"DrKGC.Furthermore,":[150],"realistic":[152],"case":[153],"study":[154],"highlights":[159],"its":[160],"interpretability":[161],"practical":[163],"utility.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-08T00:00:00"}
