{"id":"https://openalex.org/W4213457947","doi":"https://doi.org/10.1162/dint_a_00144","title":"Ensemble Making Few-Shot Learning Stronger","display_name":"Ensemble Making Few-Shot Learning Stronger","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4213457947","doi":"https://doi.org/10.1162/dint_a_00144"},"language":"en","primary_location":{"id":"doi:10.1162/dint_a_00144","is_oa":true,"landing_page_url":"https://doi.org/10.1162/dint_a_00144","pdf_url":null,"source":{"id":"https://openalex.org/S4210186383","display_name":"Data Intelligence","issn_l":"2096-7004","issn":["2096-7004","2641-435X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1162/dint_a_00144","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077528633","display_name":"Qiang Lin","orcid":"https://orcid.org/0000-0002-3842-2634"},"institutions":[{"id":"https://openalex.org/I91935597","display_name":"University of South China","ror":"https://ror.org/03mqfn238","country_code":"CN","type":"education","lineage":["https://openalex.org/I91935597"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiang Lin","raw_affiliation_strings":["Computer School, University of South China 42,1001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer School, University of South China 42,1001, China","institution_ids":["https://openalex.org/I91935597"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101666117","display_name":"Yongbin Liu","orcid":"https://orcid.org/0000-0002-3369-3101"},"institutions":[{"id":"https://openalex.org/I4210156400","display_name":"Department of Science and Technology of Hunan Province","ror":"https://ror.org/04qgr7x96","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210156400"]},{"id":"https://openalex.org/I91935597","display_name":"University of South China","ror":"https://ror.org/03mqfn238","country_code":"CN","type":"education","lineage":["https://openalex.org/I91935597"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongbin Liu","raw_affiliation_strings":["Computer School, University of South China 42,1001, China","Hunan provincial base for scientific and technological innovation cooperation, Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer School, University of South China 42,1001, China","institution_ids":["https://openalex.org/I91935597"]},{"raw_affiliation_string":"Hunan provincial base for scientific and technological innovation cooperation, Hunan, China","institution_ids":["https://openalex.org/I4210156400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319719","display_name":"Wen Wen","orcid":"https://orcid.org/0000-0002-0430-6686"},"institutions":[{"id":"https://openalex.org/I91935597","display_name":"University of South China","ror":"https://ror.org/03mqfn238","country_code":"CN","type":"education","lineage":["https://openalex.org/I91935597"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wen Wen","raw_affiliation_strings":["Computer School, University of South China 42,1001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer School, University of South China 42,1001, China","institution_ids":["https://openalex.org/I91935597"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114124493","display_name":"Zhihua Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I91935597","display_name":"University of South China","ror":"https://ror.org/03mqfn238","country_code":"CN","type":"education","lineage":["https://openalex.org/I91935597"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhihua Tao","raw_affiliation_strings":["Computer School, University of South China 42,1001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer School, University of South China 42,1001, China","institution_ids":["https://openalex.org/I91935597"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112883084","display_name":"Chunping Ouyang","orcid":"https://orcid.org/0000-0002-2154-0079"},"institutions":[{"id":"https://openalex.org/I91935597","display_name":"University of South China","ror":"https://ror.org/03mqfn238","country_code":"CN","type":"education","lineage":["https://openalex.org/I91935597"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunping Ouyang","raw_affiliation_strings":["Computer School, University of South China 42,1001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer School, University of South China 42,1001, China","institution_ids":["https://openalex.org/I91935597"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035494769","display_name":"Yaping Wan","orcid":"https://orcid.org/0000-0001-9215-5488"},"institutions":[{"id":"https://openalex.org/I91935597","display_name":"University of South China","ror":"https://ror.org/03mqfn238","country_code":"CN","type":"education","lineage":["https://openalex.org/I91935597"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaping Wan","raw_affiliation_strings":["Computer School, University of South China 42,1001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer School, University of South China 42,1001, China","institution_ids":["https://openalex.org/I91935597"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5035494769","https://openalex.org/A5077528633","https://openalex.org/A5100319719","https://openalex.org/A5101666117","https://openalex.org/A5112883084","https://openalex.org/A5114124493"],"corresponding_institution_ids":["https://openalex.org/I4210156400","https://openalex.org/I91935597"],"apc_list":null,"apc_paid":null,"fwci":2.2306,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.89268047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"4","issue":"3","first_page":"529","last_page":"551"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9957000017166138,"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":0.9919999837875366,"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":0.7761807441711426},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.6641908884048462},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.6588174104690552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6577192544937134},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5665125250816345},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5385874509811401},{"id":"https://openalex.org/keywords/economic-shortage","display_name":"Economic shortage","score":0.5047308206558228},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.4613627791404724},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.44576162099838257},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4350762665271759},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2397107183933258}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7761807441711426},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6641908884048462},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6588174104690552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6577192544937134},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5665125250816345},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5385874509811401},{"id":"https://openalex.org/C194051981","wikidata":"https://www.wikidata.org/wiki/Q1337691","display_name":"Economic shortage","level":3,"score":0.5047308206558228},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.4613627791404724},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.44576162099838257},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4350762665271759},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2397107183933258},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","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},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1162/dint_a_00144","is_oa":true,"landing_page_url":"https://doi.org/10.1162/dint_a_00144","pdf_url":null,"source":{"id":"https://openalex.org/S4210186383","display_name":"Data Intelligence","issn_l":"2096-7004","issn":["2096-7004","2641-435X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0b0bf41b318d4741a3dd85574735f2d5","is_oa":false,"landing_page_url":"https://doaj.org/article/0b0bf41b318d4741a3dd85574735f2d5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Intelligence, Vol 4, Iss 3 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1162/dint_a_00144","is_oa":true,"landing_page_url":"https://doi.org/10.1162/dint_a_00144","pdf_url":null,"source":{"id":"https://openalex.org/S4210186383","display_name":"Data Intelligence","issn_l":"2096-7004","issn":["2096-7004","2641-435X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2097117768","https://openalex.org/W2147800946","https://openalex.org/W2157331557","https://openalex.org/W2604763608","https://openalex.org/W2753160622","https://openalex.org/W2805481182","https://openalex.org/W2896457183","https://openalex.org/W2905471643","https://openalex.org/W2951615109","https://openalex.org/W2963341924","https://openalex.org/W2963741406","https://openalex.org/W2963777632","https://openalex.org/W2964105864","https://openalex.org/W2964298026","https://openalex.org/W2971136144","https://openalex.org/W2988205463","https://openalex.org/W2995589713","https://openalex.org/W3012209922","https://openalex.org/W3034251792","https://openalex.org/W3038665551","https://openalex.org/W3091905774","https://openalex.org/W3184324824","https://openalex.org/W4293412117","https://openalex.org/W4385245566","https://openalex.org/W6717697761","https://openalex.org/W6739901393","https://openalex.org/W6757508541","https://openalex.org/W6766092863","https://openalex.org/W6783596713"],"related_works":["https://openalex.org/W2794896638","https://openalex.org/W1807784185","https://openalex.org/W4390905871","https://openalex.org/W3202800081","https://openalex.org/W1909207154","https://openalex.org/W3124390867","https://openalex.org/W3101614107","https://openalex.org/W3204228978","https://openalex.org/W1514365828","https://openalex.org/W4390971112"],"abstract_inverted_index":{"Abstract":[0],"Few-shot":[1],"learning":[2,26,119],"has":[3,33],"been":[4,21],"proposed":[5],"and":[6,88,103,106],"rapidly":[7],"emerging":[8],"as":[9],"a":[10,34,38,59,71],"viable":[11],"means":[12],"for":[13,24,44,58],"completing":[14],"various":[15,65],"tasks.":[16,27],"Many":[17],"few-shot":[18,85,117],"models":[19,32],"have":[20],"widely":[22],"used":[23],"relation":[25,66,86,118],"However,":[28],"each":[29],"of":[30,36,41,84],"these":[31],"shortage":[35],"capturing":[37],"certain":[39],"aspect":[40],"semantic":[42],"features,":[43],"example,":[45],"CNN":[46],"on":[47,52,115],"long-range":[48],"dependencies":[49],"part,":[50],"Transformer":[51],"local":[53],"features.":[54,113],"It":[55],"is":[56],"difficult":[57],"single":[60],"model":[61,124],"to":[62,64,99,110],"adapt":[63],"learning,":[67],"which":[68],"results":[69],"in":[70,80],"high":[72,90],"variance":[73,91,102],"problem.":[74],"Ensemble":[75],"strategy":[76],"could":[77],"be":[78],"competitive":[79],"improving":[81],"the":[82,101,127],"accuracy":[83],"extraction":[87],"mitigating":[89],"risks.":[92],"This":[93],"paper":[94],"explores":[95],"an":[96],"ensemble":[97],"approach":[98],"reduce":[100],"introduces":[104],"fine-tuning":[105],"feature":[107],"attention":[108],"strategies":[109],"calibrate":[111],"relation-level":[112],"Results":[114],"several":[116],"tasks":[120],"show":[121],"that":[122],"our":[123],"significantly":[125],"outperforms":[126],"previous":[128],"state-of-the-art":[129],"models.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
