{"id":"https://openalex.org/W4308614401","doi":"https://doi.org/10.48550/arxiv.2211.03270","title":"Reconciliation of Pre-trained Models and Prototypical Neural Networks in Few-shot Named Entity Recognition","display_name":"Reconciliation of Pre-trained Models and Prototypical Neural Networks in Few-shot Named Entity Recognition","publication_year":2022,"publication_date":"2022-11-07","ids":{"openalex":"https://openalex.org/W4308614401","doi":"https://doi.org/10.48550/arxiv.2211.03270"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2211.03270","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.03270","pdf_url":"https://arxiv.org/pdf/2211.03270","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2211.03270","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053236889","display_name":"Youcheng Huang","orcid":"https://orcid.org/0000-0002-0888-5881"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Huang, Youcheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039239180","display_name":"Wenqiang Lei","orcid":"https://orcid.org/0000-0001-6540-0601"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei, Wenqiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100666922","display_name":"Jie Fu","orcid":"https://orcid.org/0000-0001-5622-4888"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Jie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5073535763","display_name":"Jiancheng Lv","orcid":"https://orcid.org/0000-0001-6551-3884"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lv, Jiancheng","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5053236889"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9965999722480774,"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":0.9672999978065491,"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":0.8201761245727539},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6730361580848694},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6593710780143738},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5858084559440613},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5772687196731567},{"id":"https://openalex.org/keywords/de-facto","display_name":"De facto","score":0.5589559674263},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.49152669310569763},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4819362163543701},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.45916634798049927},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41970252990722656},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4192188084125519}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8201761245727539},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6730361580848694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6593710780143738},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5858084559440613},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5772687196731567},{"id":"https://openalex.org/C2992317946","wikidata":"https://www.wikidata.org/wiki/Q712144","display_name":"De facto","level":2,"score":0.5589559674263},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.49152669310569763},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4819362163543701},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.45916634798049927},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41970252990722656},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4192188084125519},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2211.03270","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.03270","pdf_url":"https://arxiv.org/pdf/2211.03270","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2211.03270","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2211.03270","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2211.03270","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.03270","pdf_url":"https://arxiv.org/pdf/2211.03270","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2807906686","https://openalex.org/W2794909825","https://openalex.org/W4247715995","https://openalex.org/W2745001401","https://openalex.org/W2594962586","https://openalex.org/W4321353415","https://openalex.org/W4287755480","https://openalex.org/W3113607506","https://openalex.org/W2898211994"],"abstract_inverted_index":{"Incorporating":[0],"large-scale":[1],"pre-trained":[2,30,127],"models":[3,31,90,128],"with":[4,69],"the":[5,25,53,82,88,95,101,113],"prototypical":[6,43,130],"neural":[7,44,131],"networks":[8,45],"is":[9],"a":[10,33,60,67],"de-facto":[11],"paradigm":[12],"in":[13,116],"few-shot":[14,117],"named":[15],"entity":[16,119],"recognition.":[17],"Existing":[18],"methods,":[19],"unfortunately,":[20],"are":[21,92],"not":[22],"aware":[23],"of":[24,37,84],"fact":[26],"that":[27,124],"embeddings":[28],"from":[29],"contain":[32],"prominently":[34],"large":[35],"amount":[36],"information":[38],"regarding":[39],"word":[40,48],"frequencies,":[41],"biasing":[42],"against":[46],"learning":[47],"entities.":[49],"This":[50],"discrepancy":[51],"constrains":[52],"two":[54],"models'":[55],"synergy.":[56],"Thus,":[57],"we":[58],"propose":[59],"one-line-code":[61],"normalization":[62],"method":[63,86],"to":[64,94,100],"reconcile":[65],"such":[66],"mismatch":[68],"empirical":[70],"and":[71,91],"theoretical":[72],"grounds.":[73],"Our":[74],"experiments":[75],"based":[76],"on":[77,126],"nine":[78],"benchmark":[79],"datasets":[80],"show":[81],"superiority":[83],"our":[85,104],"over":[87],"counterpart":[89],"comparable":[93],"state-of-the-art":[96],"methods.":[97],"In":[98],"addition":[99],"model":[102],"enhancement,":[103],"work":[105],"also":[106],"provides":[107],"an":[108],"analytical":[109],"viewpoint":[110],"for":[111],"addressing":[112],"general":[114],"problems":[115],"name":[118],"recognition":[120],"or":[121,129],"other":[122],"tasks":[123],"rely":[125],"networks.":[132]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2022-11-13T00:00:00"}
