{"id":"https://openalex.org/W4283738859","doi":"https://doi.org/10.1017/s1351324922000286","title":"Artificial fine-tuning tasks for yes/no question answering","display_name":"Artificial fine-tuning tasks for yes/no question answering","publication_year":2022,"publication_date":"2022-06-30","ids":{"openalex":"https://openalex.org/W4283738859","doi":"https://doi.org/10.1017/s1351324922000286"},"language":"en","primary_location":{"id":"doi:10.1017/s1351324922000286","is_oa":true,"landing_page_url":"https://doi.org/10.1017/s1351324922000286","pdf_url":"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/43DE9DD063185065D9E2AB883D441922/S1351324922000286a.pdf/div-class-title-artificial-fine-tuning-tasks-for-yes-no-question-answering-div.pdf","source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/43DE9DD063185065D9E2AB883D441922/S1351324922000286a.pdf/div-class-title-artificial-fine-tuning-tasks-for-yes-no-question-answering-div.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055026410","display_name":"Dimitris Dimitriadis","orcid":"https://orcid.org/0000-0002-9404-0331"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Dimitris Dimitriadis","raw_affiliation_strings":["Aristotle University of Thessaloniki, Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0002-9404-0331","affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026561247","display_name":"Grigorios Tsoumakas","orcid":"https://orcid.org/0000-0002-7879-669X"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Grigorios Tsoumakas","raw_affiliation_strings":["Aristotle University of Thessaloniki, Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0002-7879-669X","affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5055026410"],"corresponding_institution_ids":["https://openalex.org/I21370196"],"apc_list":null,"apc_paid":null,"fwci":0.2324,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58962317,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"30","issue":"1","first_page":"73","last_page":"95"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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":0.9997000098228455,"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/T12031","display_name":"Speech and dialogue systems","score":0.975600004196167,"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/computer-science","display_name":"Computer science","score":0.9067620038986206},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7728955745697021},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6394881010055542},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.615153968334198},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5964156985282898},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5638357996940613},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5553207993507385},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.532148540019989},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5068450570106506},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43376898765563965},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4314202070236206},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.42082133889198303},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07742497324943542}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9067620038986206},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7728955745697021},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6394881010055542},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.615153968334198},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5964156985282898},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5638357996940613},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5553207993507385},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.532148540019989},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5068450570106506},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43376898765563965},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4314202070236206},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.42082133889198303},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07742497324943542},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1017/s1351324922000286","is_oa":true,"landing_page_url":"https://doi.org/10.1017/s1351324922000286","pdf_url":"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/43DE9DD063185065D9E2AB883D441922/S1351324922000286a.pdf/div-class-title-artificial-fine-tuning-tasks-for-yes-no-question-answering-div.pdf","source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1017/s1351324922000286","is_oa":true,"landing_page_url":"https://doi.org/10.1017/s1351324922000286","pdf_url":"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/43DE9DD063185065D9E2AB883D441922/S1351324922000286a.pdf/div-class-title-artificial-fine-tuning-tasks-for-yes-no-question-answering-div.pdf","source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8199999928474426,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4283738859.pdf","grobid_xml":"https://content.openalex.org/works/W4283738859.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W41647797","https://openalex.org/W1566289585","https://openalex.org/W1579838312","https://openalex.org/W1682403713","https://openalex.org/W1981208470","https://openalex.org/W2054070929","https://openalex.org/W2067624665","https://openalex.org/W2083581617","https://openalex.org/W2103247590","https://openalex.org/W2106390866","https://openalex.org/W2112282043","https://openalex.org/W2162586529","https://openalex.org/W2170872814","https://openalex.org/W2250953687","https://openalex.org/W2251939518","https://openalex.org/W2278131208","https://openalex.org/W2397326603","https://openalex.org/W2397663929","https://openalex.org/W2399756416","https://openalex.org/W2403393286","https://openalex.org/W2510358553","https://openalex.org/W2552027021","https://openalex.org/W2574026469","https://openalex.org/W2618415699","https://openalex.org/W2626154462","https://openalex.org/W2739628284","https://openalex.org/W2885197251","https://openalex.org/W2886441967","https://openalex.org/W2892217184","https://openalex.org/W2896457183","https://openalex.org/W2913962323","https://openalex.org/W2946659172","https://openalex.org/W2950784811","https://openalex.org/W2953519289","https://openalex.org/W2963323070","https://openalex.org/W2963748441","https://openalex.org/W2964175469","https://openalex.org/W2972324944","https://openalex.org/W2975059944","https://openalex.org/W2979826702","https://openalex.org/W2979860911","https://openalex.org/W2997049449","https://openalex.org/W3013517204","https://openalex.org/W3089222420","https://openalex.org/W3096673114","https://openalex.org/W3124687886","https://openalex.org/W3158716790","https://openalex.org/W4288089799","https://openalex.org/W4298165362","https://openalex.org/W6675494709","https://openalex.org/W6712515064","https://openalex.org/W6739901393","https://openalex.org/W6769627184","https://openalex.org/W6772777743"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W4381058564","https://openalex.org/W3003945460","https://openalex.org/W2964413124","https://openalex.org/W4288267738","https://openalex.org/W4206178588","https://openalex.org/W3094491777","https://openalex.org/W3214715529","https://openalex.org/W4287635093"],"abstract_inverted_index":{"Abstract":[0],"Current":[1],"research":[2],"in":[3],"yes/no":[4,27,39,71,82,179,206],"question":[5],"answering":[6],"(QA)":[7],"focuses":[8],"on":[9,18,23,173],"transfer":[10,74],"learning":[11],"techniques":[12],"and":[13,29,103,120,164,186,201],"transformer-based":[14],"models.":[15,208],"Models":[16],"trained":[17],"large":[19],"corpora":[20],"are":[21,143],"fine-tuned":[22],"tasks":[24,88,200],"similar":[25,47],"to":[26,159,175,204],"QA,":[28,56],"then":[30],"the":[31,38,58,79,114,135,139,146,149,154,161,165,178,188],"captured":[32],"knowledge":[33,76],"is":[34,183],"transferred":[35],"for":[36,57,77,89,130,145],"solving":[37],"QA":[40,180,207],"task.":[41],"Most":[42],"previous":[43],"studies":[44],"use":[45],"existing":[46,96,199],"tasks,":[48,133,153],"such":[49,87],"as":[50,193],"natural":[51],"language":[52],"inference":[53],"or":[54],"extractive":[55],"fine-tuning":[59,147],"step.":[60],"This":[61,168],"paper":[62],"follows":[63],"a":[64],"different":[65,111],"perspective,":[66],"hypothesizing":[67],"that":[68,125,142,156,182],"an":[69,170],"artificial":[70,132],"task":[72],"can":[73,195],"useful":[75],"improving":[78],"performance":[80],"of":[81,113,138],"QA.":[83],"We":[84],"introduce":[85],"three":[86,94,110],"this":[90],"purpose,":[91],"by":[92],"adapting":[93],"corresponding":[95,140,202],"tasks:":[97],"candidate":[98],"answer":[99],"validation,":[100],"sentiment":[101],"classification,":[102],"lexical":[104],"simplification.":[105],"Furthermore,":[106],"we":[107,157],"experimented":[108],"with":[109,177],"variations":[112],"BERT":[115],"model":[116],"(BERT":[117],"base,":[118],"RoBERTa,":[119],"ALBERT).":[121],"The":[122],"results":[123],"show":[124],"our":[126],"hypothesis":[127],"holds":[128],"true":[129],"all":[131],"despite":[134],"small":[136],"size":[137],"datasets":[141,203],"used":[144],"process,":[148],"differences":[150],"between":[151],"these":[152],"decisions":[155],"made":[158],"adapt":[160],"original":[162],"ones,":[163],"tasks\u2019":[166],"simplicity.":[167],"gives":[169],"alternative":[171],"perspective":[172],"how":[174],"deal":[176],"problem,":[181],"more":[184,191],"creative,":[185],"at":[187],"same":[189],"time":[190],"flexible,":[192],"it":[194],"exploit":[196],"multiple":[197],"other":[198],"improve":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-04T08:18:43.703281","created_date":"2025-10-10T00:00:00"}
