{"id":"https://openalex.org/W2590925815","doi":"https://doi.org/10.18653/v1/e17-1005","title":"When is multitask learning effective? Semantic sequence prediction under varying data conditions","display_name":"When is multitask learning effective? Semantic sequence prediction under varying data conditions","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2590925815","doi":"https://doi.org/10.18653/v1/e17-1005","mag":"2590925815"},"language":"en","primary_location":{"id":"doi:10.18653/v1/e17-1005","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/e17-1005","pdf_url":"https://www.aclweb.org/anthology/E17-1005.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 15th Conference of the European Chapter of the\n          Association for Computational Linguistics: Volume 1, Long Papers","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/E17-1005.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014924576","display_name":"H\u0117ctor Mart\u00ednez Alonso","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"H\u00e9ctor Mart\u00ednez Alonso","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5088832285","display_name":"Barbara Plank","orcid":"https://orcid.org/0000-0002-4394-1965"},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Barbara Plank","raw_affiliation_strings":["Center for Language and Cognition, University of Groningen, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Center for Language and Cognition, University of Groningen, The Netherlands","institution_ids":["https://openalex.org/I169381384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014924576"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.531,"has_fulltext":true,"cited_by_count":78,"citation_normalized_percentile":{"value":0.98542924,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"44","last_page":"53"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","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/T10028","display_name":"Topic Modeling","score":0.9973000288009644,"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":0.9955000281333923,"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/multi-task-learning","display_name":"Multi-task learning","score":0.8042703866958618},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.74444580078125},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7086476683616638},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6133254170417786},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.6045366525650024},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5566177368164062},{"id":"https://openalex.org/keywords/sequence-learning","display_name":"Sequence learning","score":0.49630314111709595},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4644218981266022},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41247954964637756}],"concepts":[{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.8042703866958618},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.74444580078125},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7086476683616638},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6133254170417786},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.6045366525650024},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5566177368164062},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.49630314111709595},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4644218981266022},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41247954964637756},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/e17-1005","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/e17-1005","pdf_url":"https://www.aclweb.org/anthology/E17-1005.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 15th Conference of the European Chapter of the\n          Association for Computational Linguistics: Volume 1, Long Papers","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/e17-1005","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/e17-1005","pdf_url":"https://www.aclweb.org/anthology/E17-1005.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 15th Conference of the European Chapter of the\n          Association for Computational Linguistics: Volume 1, Long Papers","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320320933","display_name":"Rijksuniversiteit Groningen","ror":"https://ror.org/012p63287"},{"id":"https://openalex.org/F4320337373","display_name":"Center for Information Technology","ror":"https://ror.org/03jh5a977"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2590925815.pdf","grobid_xml":"https://content.openalex.org/works/W2590925815.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1578045179","https://openalex.org/W1632114991","https://openalex.org/W1860935423","https://openalex.org/W1940872118","https://openalex.org/W2006546769","https://openalex.org/W2051390224","https://openalex.org/W2064675550","https://openalex.org/W2065157922","https://openalex.org/W2110485445","https://openalex.org/W2115792525","https://openalex.org/W2116512345","https://openalex.org/W2130903752","https://openalex.org/W2144578941","https://openalex.org/W2152463966","https://openalex.org/W2158899491","https://openalex.org/W2168963845","https://openalex.org/W2178333206","https://openalex.org/W2251311344","https://openalex.org/W2251332263","https://openalex.org/W2252024663","https://openalex.org/W2293502436","https://openalex.org/W2296283641","https://openalex.org/W2301095666","https://openalex.org/W2471347784","https://openalex.org/W2516255829","https://openalex.org/W2525907473","https://openalex.org/W2573704241","https://openalex.org/W2578454709","https://openalex.org/W2579343286","https://openalex.org/W2913340405","https://openalex.org/W2949952998","https://openalex.org/W2963042536","https://openalex.org/W2963498408","https://openalex.org/W2963842982","https://openalex.org/W2964090065","https://openalex.org/W3023071679"],"related_works":["https://openalex.org/W2803309984","https://openalex.org/W2883195674","https://openalex.org/W2072736607","https://openalex.org/W2274463100","https://openalex.org/W2043380470","https://openalex.org/W2125171914","https://openalex.org/W3080374445","https://openalex.org/W2951720331","https://openalex.org/W2964790801","https://openalex.org/W1522215732"],"abstract_inverted_index":{"Multitask":[0],"learning":[1],"has":[2],"been":[3],"applied":[4],"successfully":[5],"to":[6,29,63],"a":[7,38,46,56],"range":[8,39],"of":[9,40,83],"tasks,":[10,53],"mostly":[11],"morphosyntactic.":[12],"However,":[13],"little":[14],"is":[15,71],"known":[16],"on":[17],"when":[18],"MTL":[19,47,70],"works":[20],"and":[21,59,92],"whether":[22],"there":[23],"are":[24,77,97],"data":[25],"characteristics":[26],"that":[27,69],"help":[28],"determine":[30],"its":[31],"success.":[32],"In":[33],"this":[34],"paper":[35],"we":[36],"evaluate":[37],"semantic":[41],"sequence":[42],"labeling":[43],"tasks":[44,89],"in":[45],"setup.":[48],"We":[49],"examine":[50],"different":[51],"auxiliary":[52,88],"amongst":[54],"which":[55],"novel":[57],"setup,":[58],"correlate":[60],"their":[61],"impact":[62],"datadependent":[64],"conditions.":[65],"Our":[66],"results":[67],"show":[68],"not":[72],"always":[73],"effective,":[74],"significant":[75],"improvements":[76],"obtained":[78],"only":[79],"for":[80],"1":[81],"out":[82],"5":[84],"tasks.":[85],"When":[86],"successful,":[87],"with":[90],"compact":[91],"more":[93],"uniform":[94],"label":[95],"distributions":[96],"preferable.":[98]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":17},{"year":2018,"cited_by_count":16},{"year":2017,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}