{"id":"https://openalex.org/W4416034295","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.915","title":"Dynamic Injection of Entity Knowledge into Dense Retrievers","display_name":"Dynamic Injection of Entity Knowledge into Dense Retrievers","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416034295","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.915"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.915","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.915","pdf_url":"https://aclanthology.org/2025.findings-emnlp.915.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":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-emnlp.915.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ikuya Yamada","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ikuya Yamada","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044999802","display_name":"Ryokan Ri","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ryokan Ri","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089855423","display_name":"Takeshi Kojima","orcid":"https://orcid.org/0000-0002-4081-7854"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takeshi Kojima","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063925941","display_name":"Yusuke Iwasawa","orcid":"https://orcid.org/0000-0002-1321-2622"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yusuke Iwasawa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5074059447","display_name":"Yutaka Matsuo","orcid":"https://orcid.org/0000-0002-2070-4393"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yutaka Matsuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"16867","last_page":"16879"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.15649999678134918,"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"}},"topics":[{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.15649999678134918,"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"}},{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.1404999941587448,"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":0.13449999690055847,"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/set","display_name":"Set (abstract data type)","score":0.30070000886917114},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.29350000619888306},{"id":"https://openalex.org/keywords/knowledge-based-systems","display_name":"Knowledge-based systems","score":0.2752000093460083},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.2732999920845032},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.2623000144958496}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5278000235557556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3921999931335449},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.23600000143051147},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.23199999332427979}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-emnlp.915","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.915","pdf_url":"https://aclanthology.org/2025.findings-emnlp.915.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.915","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.915","pdf_url":"https://aclanthology.org/2025.findings-emnlp.915.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":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416034295.pdf","grobid_xml":"https://content.openalex.org/works/W4416034295.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Dense":[0],"retrievers":[1],"often":[2],"struggle":[3],"with":[4,25,55],"queries":[5],"involving":[6],"less-frequent":[7],"entities":[8],"due":[9],"to":[10,38],"their":[11],"limited":[12],"entity":[13,33,41],"knowledge.We":[14],"propose":[15],"the":[16,60,65],"Knowledgeable":[17],"Passage":[18],"Retriever":[19],"(KPR),":[20],"a":[21,26],"BERT-based":[22],"retriever":[23],"enhanced":[24],"contextentity":[27],"attention":[28],"layer":[29],"and":[30,80],"dynamically":[31],"updatable":[32],"embeddings.This":[34],"design":[35],"enables":[36],"KPR":[37,50,69],"incorporate":[39],"external":[40],"knowledge":[42],"without":[43],"retraining.Experiments":[44],"on":[45,59,64,77],"three":[46],"datasets":[47],"demonstrate":[48],"that":[49],"consistently":[51],"improves":[52],"retrieval":[53],"accuracy,":[54],"particularly":[56],"large":[57],"gains":[58],"EntityQuestions":[61],"dataset.When":[62],"built":[63],"off-the-shelf":[66],"bgebase":[67],"retriever,":[68],"achieves":[70],"state-of-the-art":[71],"performance":[72],"among":[73],"similarly":[74],"sized":[75],"models":[76],"two":[78],"datasets.Models":[79],"code":[81],"are":[82],"released":[83],"at":[84],"github.com/knowledgeable-embedding/knowledgeable-embedding.":[85]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-08T00:00:00"}
