乐胖代购免代理版

{"id":"https://openalex.org/W4386566741","doi":"https://doi.org/10.18653/v1/2023.eacl-main.122","title":"Cluster-Guided Label Generation in Extreme Multi-Label Classification","display_name":"Cluster-Guided Label Generation in Extreme Multi-Label Classification","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386566741","doi":"https://doi.org/10.18653/v1/2023.eacl-main.122"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.eacl-main.122","pdf_url":"https://aclanthology.org/2023.eacl-main.122.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2023.eacl-main.122.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109885464","display_name":"Taehee Jung","orcid":null},"institutions":[{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Taehee Jung","raw_affiliation_strings":["University of Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota","institution_ids":["https://openalex.org/I2800403580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064805948","display_name":"Joo-kyung Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joo-kyung Kim","raw_affiliation_strings":["University of Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota","institution_ids":["https://openalex.org/I2800403580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100720086","display_name":"Sung\u2010Jin Lee","orcid":"https://orcid.org/0000-0001-9348-8356"},"institutions":[{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sungjin Lee","raw_affiliation_strings":["University of Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota","institution_ids":["https://openalex.org/I2800403580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040821714","display_name":"Dongyeop Kang","orcid":"https://orcid.org/0000-0002-9021-1789"},"institutions":[{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongyeop Kang","raw_affiliation_strings":["University of Minnesota"],"affiliations":[{"raw_affiliation_string":"University of Minnesota","institution_ids":["https://openalex.org/I2800403580"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100720086"],"corresponding_institution_ids":["https://openalex.org/I2800403580"],"apc_list":null,"apc_paid":null,"fwci":0.64,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":2,"citation_normalized_percentile":{"value":0.481199,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":78,"max":84},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9952,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9952,"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":0.9708,"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":0.9506,"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-label-classification","display_name":"Multi-label classification","score":0.7773961},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.57727385}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8271171},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.7773961},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.57727385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5545762},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.53714335},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.53038067},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.47091433},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46013063},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33232564},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.06802964},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.eacl-main.122","pdf_url":"https://aclanthology.org/2023.eacl-main.122.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2302.09150","pdf_url":"https://arxiv.org/pdf/2302.09150","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.eacl-main.122","pdf_url":"https://aclanthology.org/2023.eacl-main.122.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"score":0.66,"display_name":"Quality education","id":"https://metadata.un.org/sdg/4"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":33,"referenced_works":["https://openalex.org/W1940008012","https://openalex.org/W2029517229","https://openalex.org/W2121227244","https://openalex.org/W2187089797","https://openalex.org/W2422823951","https://openalex.org/W2751120573","https://openalex.org/W2886305600","https://openalex.org/W2908510526","https://openalex.org/W2938704169","https://openalex.org/W2950352656","https://openalex.org/W2950801772","https://openalex.org/W2953273646","https://openalex.org/W2963096510","https://openalex.org/W2963248507","https://openalex.org/W2963631426","https://openalex.org/W2998436114","https://openalex.org/W3001279689","https://openalex.org/W3009703289","https://openalex.org/W3034999214","https://openalex.org/W3037422790","https://openalex.org/W3039729104","https://openalex.org/W3093858897","https://openalex.org/W3165920028","https://openalex.org/W3175161202","https://openalex.org/W3177355874","https://openalex.org/W3199241049","https://openalex.org/W3211566171","https://openalex.org/W4226055008","https://openalex.org/W4285167814","https://openalex.org/W4285179439","https://openalex.org/W4287887115","https://openalex.org/W4288089799","https://openalex.org/W4292779060"],"related_works":["https://openalex.org/W4306674287","https://openalex.org/W4286629047","https://openalex.org/W4224009465","https://openalex.org/W2961085424","https://openalex.org/W2912288872","https://openalex.org/W2383319832","https://openalex.org/W2380207131","https://openalex.org/W2358034992","https://openalex.org/W2351992004","https://openalex.org/W2030492936"],"abstract_inverted_index":{"For":[0],"extreme":[1],"multi-label":[2],"classification":[3,108],"(XMC),":[4],"existing":[5],"classification-based":[6],"models":[7],"poorly":[8],"per-":[9],"form":[10],"for":[11,96],"tail":[12,113],"labels":[13,51],"and":[14,24,28,88,109,115],"often":[15],"ignore":[16],"the":[17,53,97,107,119],"semantic":[18],"relations":[19],"among":[20],"labels,":[21,114],"like":[22],"treating\"Wikipedia\"":[23],"\"Wiki\"":[25],"as":[26,37],"independent":[27],"separate":[29],"labels.":[30,80,138],"In":[31,127],"this":[32],"paper,":[33],"we":[34,43,130],"cast":[35],"XMC":[36,125],"a":[38],"generation":[39,71,110],"task":[40],"(XLGen),":[41],"where":[42],"benefit":[44],"from":[45,52],"pre-trained":[46],"text-to-text":[47],"models.":[48],"However,":[49],"generating":[50],"extremely":[54],"large":[55],"label":[56,70,73,86],"space":[57],"is":[58,141],"challenging":[59],"without":[60],"any":[61],"constraints":[62],"or":[63],"guidance.":[64],"We,":[65],"therefore,":[66],"propose":[67],"to":[68,76],"guide":[69],"using":[72,89],"cluster":[74,103],"information":[75],"hierarchically":[77],"generate":[78],"lower-level":[79],"We":[81],"also":[82,116,131],"find":[83,132],"that":[84],"frequency-based":[85],"ordering":[87],"decoding":[90],"ensemble":[91],"methods":[92],"are":[93],"critical":[94],"factors":[95],"improvements":[98],"in":[99,122],"XLGen.":[100],"XLGen":[101,133],"with":[102],"guidance":[104],"significantly":[105],"outperforms":[106],"baselines":[111],"on":[112],"generally":[117],"improves":[118],"overall":[120],"performance":[121],"four":[123],"popular":[124],"benchmarks.":[126],"human":[128],"evaluation,":[129],"generates":[134],"unseen":[135],"but":[136],"plausible":[137],"Our":[139],"code":[140],"now":[142],"available":[143],"at":[144],"https://":[145],"github.com/alexa/xlgen-eacl-2023.":[146]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4386566741","counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-01-17T05:00:10.870801","created_date":"2023-09-10"}