{"id":"https://openalex.org/W2905548899","doi":"https://doi.org/10.1609/aaai.v33i01.33018360","title":"Dual-View Ranking with Hardness Assessment for Zero-Shot Learning","display_name":"Dual-View Ranking with Hardness Assessment for Zero-Shot Learning","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2905548899","doi":"https://doi.org/10.1609/aaai.v33i01.33018360","mag":"2905548899"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33018360","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018360","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4850/4723","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4850/4723","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035519525","display_name":"Yuchen Guo","orcid":"https://orcid.org/0000-0001-9808-9805"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuchen Guo","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057732142","display_name":"Guiguang Ding","orcid":"https://orcid.org/0000-0003-0137-9975"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guiguang Ding","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046605531","display_name":"Jungong Han","orcid":"https://orcid.org/0000-0003-4361-956X"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jungong Han","raw_affiliation_strings":["Lancaster University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lancaster University","institution_ids":["https://openalex.org/I67415387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011301418","display_name":"Xiaohan Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohan Ding","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051149140","display_name":"Sicheng Zhao","orcid":"https://orcid.org/0000-0001-5843-6411"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sicheng Zhao","raw_affiliation_strings":["University of California, Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100401164","display_name":"Zheng Wang","orcid":"https://orcid.org/0000-0003-3846-9157"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Wang","raw_affiliation_strings":["University of Science and Technology Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology Beijing","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054311881","display_name":"Chenggang Yan","orcid":"https://orcid.org/0000-0003-1204-0512"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenggang Yan","raw_affiliation_strings":["Hangzhou Dianzi University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080722708","display_name":"Qionghai Dai","orcid":"https://orcid.org/0000-0001-7043-3061"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qionghai Dai","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5035519525"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.3298,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.85258359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"33","issue":"01","first_page":"8360","last_page":"8367"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9976999759674072,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9976999759674072,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9399999976158142,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.8367229700088501},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.662016749382019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6312662363052368},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5876059532165527},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5698937773704529},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5595163702964783},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.543264627456665},{"id":"https://openalex.org/keywords/ranking-svm","display_name":"Ranking SVM","score":0.5244864821434021},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.471076637506485},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4685198962688446},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45520734786987305},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4395011365413666},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.43538007140159607},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.42978179454803467},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3601246476173401},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3031728267669678},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06973192095756531}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.8367229700088501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.662016749382019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6312662363052368},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5876059532165527},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5698937773704529},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5595163702964783},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.543264627456665},{"id":"https://openalex.org/C124975894","wikidata":"https://www.wikidata.org/wiki/Q7293290","display_name":"Ranking SVM","level":3,"score":0.5244864821434021},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.471076637506485},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4685198962688446},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45520734786987305},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4395011365413666},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.43538007140159607},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.42978179454803467},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3601246476173401},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3031728267669678},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06973192095756531},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v33i01.33018360","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018360","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4850/4723","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33018360","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018360","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4850/4723","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6100000143051147,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G187184461","display_name":null,"funder_award_id":"61571269","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2311577451","display_name":null,"funder_award_id":"No. 61571269","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2778187103","display_name":null,"funder_award_id":"BX20180172","funder_id":"https://openalex.org/F4320335768","funder_display_name":"National Postdoctoral Program for Innovative Talents"},{"id":"https://openalex.org/G3537034801","display_name":null,"funder_award_id":"2018T110100, 2017M610897","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G3667872166","display_name":null,"funder_award_id":"2018YFC0806900","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3770199858","display_name":null,"funder_award_id":"2017M610897","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G5574925684","display_name":null,"funder_award_id":"61701273","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8087118743","display_name":null,"funder_award_id":"61671196","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8290336390","display_name":null,"funder_award_id":"61525206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8883308132","display_name":null,"funder_award_id":"61327902","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320335768","display_name":"National Postdoctoral Program for Innovative Talents","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2905548899.pdf","grobid_xml":"https://content.openalex.org/works/W2905548899.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W93016980","https://openalex.org/W652269744","https://openalex.org/W1797268635","https://openalex.org/W1858576077","https://openalex.org/W1960364170","https://openalex.org/W2070148066","https://openalex.org/W2112912048","https://openalex.org/W2123024445","https://openalex.org/W2124033848","https://openalex.org/W2128532956","https://openalex.org/W2141350700","https://openalex.org/W2149557440","https://openalex.org/W2171061940","https://openalex.org/W2194775991","https://openalex.org/W2209594346","https://openalex.org/W2289084343","https://openalex.org/W2334493732","https://openalex.org/W2341497066","https://openalex.org/W2400717490","https://openalex.org/W2405338641","https://openalex.org/W2514265125","https://openalex.org/W2594407953","https://openalex.org/W2596142952","https://openalex.org/W2605805765","https://openalex.org/W2609698233","https://openalex.org/W2611632661","https://openalex.org/W2725671465","https://openalex.org/W2738760914","https://openalex.org/W2741634395","https://openalex.org/W2791332680","https://openalex.org/W2791906491","https://openalex.org/W2799215068","https://openalex.org/W2807795836","https://openalex.org/W2887241700","https://openalex.org/W2950700180","https://openalex.org/W2962716320","https://openalex.org/W2962762077","https://openalex.org/W2962903908","https://openalex.org/W2963499153","https://openalex.org/W2963516811","https://openalex.org/W2963656735","https://openalex.org/W2963784503","https://openalex.org/W2964086552","https://openalex.org/W2964162033","https://openalex.org/W3099206234","https://openalex.org/W3100093508","https://openalex.org/W4212863985","https://openalex.org/W4249965322","https://openalex.org/W6638319203","https://openalex.org/W6674877697","https://openalex.org/W6678360021","https://openalex.org/W6678470764","https://openalex.org/W6680829553","https://openalex.org/W6685405407","https://openalex.org/W6687483927","https://openalex.org/W6703186702","https://openalex.org/W6734394377","https://openalex.org/W6737234332","https://openalex.org/W6737680032","https://openalex.org/W6742301467","https://openalex.org/W6748084136","https://openalex.org/W6754068695"],"related_works":["https://openalex.org/W2036613096","https://openalex.org/W2744293020","https://openalex.org/W3127142483","https://openalex.org/W2974774628","https://openalex.org/W2237303429","https://openalex.org/W2293317945","https://openalex.org/W4318960487","https://openalex.org/W161037631","https://openalex.org/W1786507113","https://openalex.org/W3093924713"],"abstract_inverted_index":{"Zero-shot":[0],"learning":[1,153],"(ZSL)":[2],"is":[3,46,91,173],"to":[4,34,47,83,96,102,125,130,195,225,231,240],"build":[5],"recognition":[6],"models":[7],"for":[8,18,71,106,151,157,166,257],"previously":[9],"unseen":[10],"target":[11,36],"classes":[12,29,63],"which":[13,94,123,172,227,238],"have":[14],"no":[15],"labeled":[16,32,61],"data":[17],"training":[19,108,201,232],"by":[20,78,141,160,169],"transferring":[21],"knowledge":[22],"from":[23,119,136],"some":[24],"other":[25,104,121,138],"related":[26],"auxiliary":[27],"source":[28,62],"with":[30,38],"abundant":[31],"samples":[33,55,212,233],"the":[35,42,60,66,79,85,98,103,114,120,127,134,137,178,198,255],"ones":[37,208],"class":[39,57,69],"attributes":[40],"as":[41],"bridge.":[43],"The":[44],"key":[45],"learn":[48,84],"a":[49,72,107,131,145,167,220,241],"similarity":[50],"based":[51,89,234],"ranking":[52,88,115,155,164],"function":[53],"between":[54,180],"and":[56,163,182,244],"labels":[58,105,156],"using":[59,204,210],"so":[64],"that":[65,113,189,252],"proper":[67],"(unseen)":[68],"label":[70,100,132,168],"test":[73],"sample":[74,221],"can":[75,116],"be":[76,117],"identified":[77],"function.":[80],"In":[81,184,214],"order":[82],"function,":[86],"single-view":[87],"loss":[90,150],"widely":[92],"used":[93],"aims":[95,124],"rank":[97],"true":[99],"prior":[101],"sample.":[109],"However,":[110],"we":[111,143,186,217],"argue":[112],"performed":[118],"view,":[122],"place":[126],"images":[128,135,165,181],"belonging":[129],"before":[133],"classes.":[139,183],"Motivated":[140],"it,":[142],"propose":[144],"novel":[146],"DuAl-view":[147],"RanKing":[148],"(DARK)":[149],"zeroshot":[152],"simultaneously":[154],"an":[158],"image":[159],"point-to-point":[161],"metric":[162],"pointto-set":[170],"metric,":[171],"capable":[174],"of":[175,200],"better":[176],"modeling":[177],"relationship":[179],"addition,":[185],"also":[187,218],"notice":[188],"previous":[190],"ZSL":[191,226,246],"approaches":[192],"mostly":[193],"fail":[194],"well":[196],"exploit":[197],"hardness":[199,222],"samples,":[202],"either":[203],"only":[205],"very":[206],"hard":[207],"or":[209],"all":[211],"indiscriminately.":[213],"this":[215],"work,":[216],"introduce":[219],"assessment":[223],"method":[224],"assigns":[228],"different":[229],"weights":[230],"on":[235,249],"their":[236],"hardness,":[237],"leads":[239],"more":[242],"accurate":[243],"robust":[245],"model.":[247],"Experiments":[248],"benchmarks":[250],"demonstrate":[251],"DARK":[253],"outperforms":[254],"state-of-the-arts":[256],"(generalized)":[258],"ZSL.":[259]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}