{"id":"https://openalex.org/W3200759354","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533990","title":"Multitask Learning Using BERT with Task-Embedded Attention","display_name":"Multitask Learning Using BERT with Task-Embedded Attention","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200759354","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533990","mag":"3200759354"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533990","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533990","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://ruj.uj.edu.pl/xmlui/handle/item/284504","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025532190","display_name":"\u0141ukasz Maziarka","orcid":"https://orcid.org/0000-0001-6947-8131"},"institutions":[{"id":"https://openalex.org/I126596746","display_name":"Jagiellonian University","ror":"https://ror.org/03bqmcz70","country_code":"PL","type":"education","lineage":["https://openalex.org/I126596746"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Lukasz Maziarka","raw_affiliation_strings":["Jagiellonian University"],"affiliations":[{"raw_affiliation_string":"Jagiellonian University","institution_ids":["https://openalex.org/I126596746"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078152358","display_name":"Tomasz Danel","orcid":"https://orcid.org/0000-0001-6053-0028"},"institutions":[{"id":"https://openalex.org/I126596746","display_name":"Jagiellonian University","ror":"https://ror.org/03bqmcz70","country_code":"PL","type":"education","lineage":["https://openalex.org/I126596746"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Tomasz Danel","raw_affiliation_strings":["Jagiellonian University"],"affiliations":[{"raw_affiliation_string":"Jagiellonian University","institution_ids":["https://openalex.org/I126596746"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025532190"],"corresponding_institution_ids":["https://openalex.org/I126596746"],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64366627,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9975000023841858,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.8560786247253418},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.8186435103416443},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7590636014938354},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7071003913879395},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6083352565765381},{"id":"https://openalex.org/keywords/spare-part","display_name":"Spare part","score":0.5094905495643616},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.49006330966949463},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4868113696575165},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47195330262184143}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8560786247253418},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.8186435103416443},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7590636014938354},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7071003913879395},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6083352565765381},{"id":"https://openalex.org/C194648553","wikidata":"https://www.wikidata.org/wiki/Q1364774","display_name":"Spare part","level":2,"score":0.5094905495643616},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.49006330966949463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4868113696575165},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47195330262184143},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533990","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533990","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:ruj.uj.edu.pl:item/284504","is_oa":true,"landing_page_url":"https://ruj.uj.edu.pl/xmlui/handle/item/284504","pdf_url":null,"source":{"id":"https://openalex.org/S4306400316","display_name":"Homo Politicus (Academy of Humanities and Economics in Lodz)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"publikacja pokonferencyjna"}],"best_oa_location":{"id":"pmh:oai:ruj.uj.edu.pl:item/284504","is_oa":true,"landing_page_url":"https://ruj.uj.edu.pl/xmlui/handle/item/284504","pdf_url":null,"source":{"id":"https://openalex.org/S4306400316","display_name":"Homo Politicus (Academy of Humanities and Economics in Lodz)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"publikacja pokonferencyjna"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.41999998688697815,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G3626668378","display_name":null,"funder_award_id":"2019/35/N/ST6/02125","funder_id":"https://openalex.org/F4320322650","funder_display_name":"Narodowym Centrum Nauki"}],"funders":[{"id":"https://openalex.org/F4320322650","display_name":"Narodowym Centrum Nauki","ror":"https://ror.org/03ha2q922"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W131533222","https://openalex.org/W1599016936","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2194775991","https://openalex.org/W2251939518","https://openalex.org/W2295072214","https://openalex.org/W2462831000","https://openalex.org/W2613904329","https://openalex.org/W2626778328","https://openalex.org/W2739351760","https://openalex.org/W2896457183","https://openalex.org/W2911300548","https://openalex.org/W2923014074","https://openalex.org/W2949718784","https://openalex.org/W2962739339","https://openalex.org/W2963168538","https://openalex.org/W2963310665","https://openalex.org/W2963748441","https://openalex.org/W2963846996","https://openalex.org/W2963854351","https://openalex.org/W2964265128","https://openalex.org/W2964303773","https://openalex.org/W2964308564","https://openalex.org/W2965373594","https://openalex.org/W2970597249","https://openalex.org/W2972324944","https://openalex.org/W2978670439","https://openalex.org/W3007488165","https://openalex.org/W3104033643","https://openalex.org/W3153675281","https://openalex.org/W4287824654","https://openalex.org/W4298395628","https://openalex.org/W4322588812","https://openalex.org/W4385245566","https://openalex.org/W6605323724","https://openalex.org/W6635469476","https://openalex.org/W6679434410","https://openalex.org/W6679436768","https://openalex.org/W6691459498","https://openalex.org/W6737236263","https://openalex.org/W6737778391","https://openalex.org/W6755406732","https://openalex.org/W6759579507","https://openalex.org/W6763367864","https://openalex.org/W6763509872","https://openalex.org/W6763701032","https://openalex.org/W6766673545","https://openalex.org/W6771917389","https://openalex.org/W6774009640","https://openalex.org/W6777155081","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4319309271","https://openalex.org/W3200361725","https://openalex.org/W4213073923","https://openalex.org/W4362598831","https://openalex.org/W2911300548","https://openalex.org/W3200759354","https://openalex.org/W4312444067","https://openalex.org/W2964319599","https://openalex.org/W4280534654"],"abstract_inverted_index":{"Multitask":[0],"learning":[1],"helps":[2],"to":[3,18,41,53,59,71,94,110],"obtain":[4],"a":[5,12,32,68,73,77,103],"meaningful":[6],"representation":[7],"of":[8,15,106],"the":[9,20,88,95,111,123],"data,":[10],"retaining":[11],"small":[13],"number":[14,105],"parameters":[16,108],"needed":[17],"train":[19,72],"model.":[21],"In":[22,63],"natural":[23],"language":[24],"processing,":[25],"models":[26],"often":[27,57],"reach":[28],"as":[29,31],"many":[30],"few":[33],"hundred":[34],"million":[35],"trainable":[36],"parameters,":[37],"which":[38,80],"makes":[39],"adaptations":[40],"new":[42,69],"tasks":[43,51],"computationally":[44],"infeasible.":[45],"Creating":[46],"shareable":[47],"layers":[48],"for":[49],"multiple":[50],"allows":[52],"spare":[54],"resources":[55],"and":[56],"leads":[58],"better":[60],"data":[61],"representation.":[62],"this":[64],"work,":[65],"we":[66,81,90],"propose":[67],"approach":[70],"BERT":[74,113],"model":[75,114],"in":[76,122],"multitask":[78],"setup,":[79],"call":[82],"EmBERT.":[83],"To":[84],"introduce":[85],"information":[86],"about":[87],"task,":[89],"inject":[91],"task-specific":[92],"embeddings":[93],"multi-head":[96],"attention":[97],"layers.":[98],"Our":[99],"modified":[100],"architecture":[101],"requires":[102],"minimal":[104],"additional":[107],"relative":[109],"original":[112],"(+0.025%":[115],"per":[116],"task)":[117],"while":[118],"achieving":[119],"state-of-the-art":[120],"results":[121],"GLUE":[124],"benchmark.":[125]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}