{"id":"https://openalex.org/W4385301567","doi":"https://doi.org/10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00349","title":"Sequence Labelling Using Multi-Task Learning with Random Connections","display_name":"Sequence Labelling Using Multi-Task Learning with Random Connections","publication_year":2022,"publication_date":"2022-12-01","ids":{"openalex":"https://openalex.org/W4385301567","doi":"https://doi.org/10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00349"},"language":"en","primary_location":{"id":"doi:10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00349","doi":"https://doi.org/10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00349","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00349","pdf_url":null,"source":{"id":"https://openalex.org/S7407088925","display_name":"IEEE Smart World Congress (SWC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032114998","display_name":"Renwei Ou","orcid":"https://orcid.org/0000-0002-9972-0002","observed_orcids":["https://orcid.org/0000-0002-9972-0002"]},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Renwei Ou","raw_affiliation_strings":["King\u2019s College London,Department of Informatics,London,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King\u2019s College London,Department of Informatics,London,United Kingdom","institution_ids":["https://openalex.org/I183935753"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5032114998"],"corresponding_institution_ids":["https://openalex.org/I183935753"],"apc_list":null,"apc_paid":null,"fwci":0.2095,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.39292485,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2498","last_page":"2505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.5166000127792358,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.5166000127792358,"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":0.4009000062942505,"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":0.05480000004172325,"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/multi-task-learning","display_name":"multi-task learning","score":0.9710000157356262},{"id":"https://openalex.org/keywords/sequence-labeling","display_name":"sequence labeling","score":0.9980000257492065},{"id":"https://openalex.org/keywords/task-balancing","display_name":"task balancing","score":0.7039999961853027},{"id":"https://openalex.org/keywords/random-connections","display_name":"random connections","score":0.8149999976158142},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"named entity recognition","score":0.777999997138977},{"id":"https://openalex.org/keywords/part-of-speech-tagging","display_name":"part-of-speech tagging","score":0.9990000128746033},{"id":"https://openalex.org/keywords/chunking","display_name":"chunking","score":0.9869999885559082},{"id":"https://openalex.org/keywords/task-specific-features","display_name":"task-specific features","score":0.5740000009536743}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7367819547653198},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7011382579803467},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6861622333526611},{"id":"https://openalex.org/C2780523633","wikidata":"https://www.wikidata.org/wiki/Q380709","display_name":"Labelling","level":2,"score":0.6805583834648132},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.41512760519981384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.361179918050766},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1038462221622467},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0759982168674469},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C73484699","wikidata":"https://www.wikidata.org/wiki/Q161733","display_name":"Criminology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00349","doi":"https://doi.org/10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00349","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00349","pdf_url":null,"source":{"id":"https://openalex.org/S7407088925","display_name":"IEEE Smart World Congress (SWC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W166521796","https://openalex.org/W1522301498","https://openalex.org/W1632114991","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2117130368","https://openalex.org/W2144578941","https://openalex.org/W2516255829","https://openalex.org/W2556468274","https://openalex.org/W2609130030","https://openalex.org/W2767434619","https://openalex.org/W2788283425","https://openalex.org/W2798465082","https://openalex.org/W2809290718","https://openalex.org/W2895387432","https://openalex.org/W2896457183","https://openalex.org/W2913340405","https://openalex.org/W2952230511","https://openalex.org/W2962902328","https://openalex.org/W2963186636","https://openalex.org/W2963341956","https://openalex.org/W2963430933","https://openalex.org/W2963677766","https://openalex.org/W2966182616","https://openalex.org/W2998103904","https://openalex.org/W3046794377","https://openalex.org/W3080189354","https://openalex.org/W3120363868","https://openalex.org/W3141797743","https://openalex.org/W3164522113","https://openalex.org/W3173197807","https://openalex.org/W6742058293"],"related_works":["https://openalex.org/W2823875838","https://openalex.org/W2887924958","https://openalex.org/W2271496879","https://openalex.org/W3046794377","https://openalex.org/W3213800435","https://openalex.org/W2975637340","https://openalex.org/W2949369097","https://openalex.org/W2560720892","https://openalex.org/W2592170186","https://openalex.org/W4386229812"],"abstract_inverted_index":{"Multi-Task":[0],"Learning":[1],"(MTL)":[2],"has":[3],"received":[4],"much":[5],"attention":[6,70],"in":[7,12,26],"research":[8],"about":[9],"its":[10,17],"usage":[11],"sequence":[13,136],"labelling":[14,137],"due":[15],"to":[16,36,62,71,81,95,99,112,151],"high":[18],"generalisation":[19],"performance":[20,143],"and":[21,147,176],"time-saving":[22],"characteristics.":[23],"The":[24],"parameters":[25],"the":[27,39,42,53,86,125,145,152,163],"shared":[28,65],"layer":[29],"of":[30,41,52,128],"MTL":[31,55,87,157],"models":[32],"are":[33,46],"often":[34],"challenging":[35],"update":[37],"since":[38],"gradients":[40],"various":[43],"tasks\u2019":[44],"losses":[45],"typically":[47],"not":[48],"equal.":[49],"However,":[50],"most":[51],"previous":[54,153],"approaches":[56],"mainly":[57],"concentrated":[58],"on":[59,134,162,173],"architectural":[60],"optimisation":[61],"extract":[63],"adequate":[64],"knowledge":[66],"while":[67,168],"paying":[68],"little":[69],"task":[72,130,167],"balancing.":[73],"To":[74],"fill":[75],"this":[76],"gap,":[77],"our":[78,115,141,156],"approach":[79],"is":[80],"introduce":[82],"gate":[83],"units":[84],"into":[85],"model":[88,116,122,158],"so":[89],"that":[90,114],"it":[91],"may":[92],"dynamically":[93],"learn":[94],"assign":[96],"different":[97],"weights":[98],"specific":[100],"tasks.":[101,138,178],"We":[102,139],"also":[103,169],"use":[104],"a":[105],"simple":[106],"but":[107],"effective":[108],"random":[109],"connection":[110],"mechanism":[111],"ensure":[113],"learns":[117],"enough":[118],"task-specific":[119],"features.":[120],"Our":[121],"allows":[123],"for":[124],"dynamic":[126],"adjustment":[127],"each":[129],"weight":[131],"when":[132],"trained":[133],"several":[135],"evaluated":[140],"model\u2019s":[142],"using":[144],"CoNLL-2000":[146],"CoNLL-2003":[148],"datasets.":[149],"Compared":[150],"baseline":[154],"methods,":[155],"achieves":[159],"state-of-the-art":[160],"results":[161],"named":[164],"entity":[165],"recognition":[166],"receiving":[170],"competitive":[171],"scores":[172],"part-of-speech":[174],"tagging":[175],"chunking":[177]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2023-07-28T00:00:00"}