{"id":"https://openalex.org/W2970771982","doi":"https://doi.org/10.18653/v1/d19-1371","title":"SciBERT: A Pretrained Language Model for Scientific Text","display_name":"SciBERT: A Pretrained Language Model for Scientific Text","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2970771982","doi":"https://doi.org/10.18653/v1/d19-1371","mag":"2970771982"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d19-1371","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-1371","pdf_url":"https://www.aclweb.org/anthology/D19-1371.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":"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D19-1371.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090038537","display_name":"Iz Beltagy","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156221","display_name":"Allen Institute for Artificial Intelligence","ror":"https://ror.org/05w520734","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210156221"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Iz Beltagy","raw_affiliation_strings":["Allen Institute for Artificial Intelligence, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Allen Institute for Artificial Intelligence, Seattle, WA, USA","institution_ids":["https://openalex.org/I4210156221"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066588555","display_name":"Kyle Lo","orcid":"https://orcid.org/0000-0002-1804-2853"},"institutions":[{"id":"https://openalex.org/I4210156221","display_name":"Allen Institute for Artificial Intelligence","ror":"https://ror.org/05w520734","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210156221"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyle Lo","raw_affiliation_strings":["Allen Institute for Artificial Intelligence, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Allen Institute for Artificial Intelligence, Seattle, WA, USA","institution_ids":["https://openalex.org/I4210156221"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064858748","display_name":"Arman Cohan","orcid":"https://orcid.org/0000-0002-8954-2724"},"institutions":[{"id":"https://openalex.org/I4210156221","display_name":"Allen Institute for Artificial Intelligence","ror":"https://ror.org/05w520734","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210156221"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arman Cohan","raw_affiliation_strings":["Allen Institute for Artificial Intelligence, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Allen Institute for Artificial Intelligence, Seattle, WA, USA","institution_ids":["https://openalex.org/I4210156221"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5090038537"],"corresponding_institution_ids":["https://openalex.org/I4210156221"],"apc_list":null,"apc_paid":null,"fwci":181.1093,"has_fulltext":true,"cited_by_count":2931,"citation_normalized_percentile":{"value":0.9998314,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3613","last_page":"3618"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9979000091552734,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7816585898399353},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6513878107070923},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5830199718475342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5164878368377686},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.35958153009414673}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7816585898399353},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6513878107070923},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5830199718475342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5164878368377686},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.35958153009414673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d19-1371","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-1371","pdf_url":"https://www.aclweb.org/anthology/D19-1371.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":"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d19-1371","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-1371","pdf_url":"https://www.aclweb.org/anthology/D19-1371.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":"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2970771982.pdf","grobid_xml":"https://content.openalex.org/works/W2970771982.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1932742904","https://openalex.org/W2047782770","https://openalex.org/W2147994374","https://openalex.org/W2163107094","https://openalex.org/W2169099542","https://openalex.org/W2279376656","https://openalex.org/W2346452181","https://openalex.org/W2396881363","https://openalex.org/W2525778437","https://openalex.org/W2552110825","https://openalex.org/W2738180183","https://openalex.org/W2793978524","https://openalex.org/W2801930304","https://openalex.org/W2808556605","https://openalex.org/W2887672952","https://openalex.org/W2896457183","https://openalex.org/W2911489562","https://openalex.org/W2925863688","https://openalex.org/W2937845937","https://openalex.org/W2952867657","https://openalex.org/W2962739339","https://openalex.org/W2962815673","https://openalex.org/W2963026768","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963571341","https://openalex.org/W2963691697","https://openalex.org/W2963716420","https://openalex.org/W2963718112","https://openalex.org/W2964121744","https://openalex.org/W2964179635","https://openalex.org/W3105491236","https://openalex.org/W3106224367","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2382290278","https://openalex.org/W2350741829","https://openalex.org/W2130043461","https://openalex.org/W2530322880","https://openalex.org/W3192589309"],"abstract_inverted_index":{"Iz":[0],"Beltagy,":[1],"Kyle":[2],"Lo,":[3],"Arman":[4],"Cohan.":[5],"Proceedings":[6],"of":[7],"the":[8,19],"2019":[9],"Conference":[10,23],"on":[11,24],"Empirical":[12],"Methods":[13],"in":[14],"Natural":[15,25],"Language":[16,26],"Processing":[17,27],"and":[18],"9th":[20],"International":[21],"Joint":[22],"(EMNLP-IJCNLP).":[28],"2019.":[29]},"counts_by_year":[{"year":2026,"cited_by_count":85},{"year":2025,"cited_by_count":488},{"year":2024,"cited_by_count":496},{"year":2023,"cited_by_count":605},{"year":2022,"cited_by_count":463},{"year":2021,"cited_by_count":530},{"year":2020,"cited_by_count":241},{"year":2019,"cited_by_count":21},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}