{"id":"https://openalex.org/W4388955690","doi":"https://doi.org/10.1145/3624918.3625330","title":"Selecting which Dense Retriever to use for Zero-Shot Search","display_name":"Selecting which Dense Retriever to use for Zero-Shot Search","publication_year":2023,"publication_date":"2023-11-23","ids":{"openalex":"https://openalex.org/W4388955690","doi":"https://doi.org/10.1145/3624918.3625330"},"language":"en","primary_location":{"id":"doi:10.1145/3624918.3625330","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3624918.3625330","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102951469","display_name":"Ekaterina Khramtsova","orcid":"https://orcid.org/0000-0001-7531-4491"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Ekaterina Khramtsova","raw_affiliation_strings":["University of Queensland, Australia"],"raw_orcid":"https://orcid.org/0000-0001-7531-4491","affiliations":[{"raw_affiliation_string":"University of Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012958162","display_name":"Shengyao Zhuang","orcid":"https://orcid.org/0000-0002-6711-0955"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shengyao Zhuang","raw_affiliation_strings":["The University of Queensland, Australia"],"raw_orcid":"https://orcid.org/0000-0002-6711-0955","affiliations":[{"raw_affiliation_string":"The University of Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014648528","display_name":"Mahsa Baktashmotlagh","orcid":"https://orcid.org/0000-0001-5255-8194"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mahsa Baktashmotlagh","raw_affiliation_strings":["University of Queensland, Australia"],"raw_orcid":"https://orcid.org/0000-0001-5255-8194","affiliations":[{"raw_affiliation_string":"University of Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053022251","display_name":"Xi Wang","orcid":"https://orcid.org/0009-0002-1724-7694"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Wang","raw_affiliation_strings":["Neusoft, China"],"raw_orcid":"https://orcid.org/0009-0002-1724-7694","affiliations":[{"raw_affiliation_string":"Neusoft, China","institution_ids":["https://openalex.org/I4210134419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076031002","display_name":"Guido Zuccon","orcid":"https://orcid.org/0000-0003-0271-5563"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guido Zuccon","raw_affiliation_strings":["The University of Queensland, Australia"],"raw_orcid":"https://orcid.org/0000-0003-0271-5563","affiliations":[{"raw_affiliation_string":"The University of Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102951469"],"corresponding_institution_ids":["https://openalex.org/I165143802"],"apc_list":null,"apc_paid":null,"fwci":1.0225,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81714358,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"223","last_page":"233"},"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":0.9991999864578247,"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":0.9991999864578247,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9990000128746033,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7623922824859619},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.6446558237075806},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.6301349401473999},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.616274356842041},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.5860361456871033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.528872013092041},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5107979774475098},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4182170033454895},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41494908928871155},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3627917170524597},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35399284958839417},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16660481691360474}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7623922824859619},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.6446558237075806},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.6301349401473999},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.616274356842041},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.5860361456871033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.528872013092041},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5107979774475098},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4182170033454895},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41494908928871155},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3627917170524597},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35399284958839417},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16660481691360474},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3624918.3625330","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3624918.3625330","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3028592866","display_name":null,"funder_award_id":"2020AAA0109400","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W398859631","https://openalex.org/W1525068081","https://openalex.org/W1966835268","https://openalex.org/W1969118846","https://openalex.org/W1977081768","https://openalex.org/W1980730196","https://openalex.org/W2024463435","https://openalex.org/W2034441832","https://openalex.org/W2036181041","https://openalex.org/W2068902033","https://openalex.org/W2087818911","https://openalex.org/W2112021481","https://openalex.org/W2956875312","https://openalex.org/W2970641574","https://openalex.org/W3034238904","https://openalex.org/W3034664137","https://openalex.org/W3134665270","https://openalex.org/W3154670582","https://openalex.org/W3156836409","https://openalex.org/W3175526344","https://openalex.org/W3180332766","https://openalex.org/W3198073108","https://openalex.org/W3198691721","https://openalex.org/W4200635123","https://openalex.org/W4206121183","https://openalex.org/W4226325130"],"related_works":["https://openalex.org/W4287241967","https://openalex.org/W3144173820","https://openalex.org/W4317548404","https://openalex.org/W3022007134","https://openalex.org/W2949671220","https://openalex.org/W2130553454","https://openalex.org/W2033364610","https://openalex.org/W2797776314","https://openalex.org/W3163689946","https://openalex.org/W4390190783"],"abstract_inverted_index":{"We":[0],"propose":[1],"the":[2,51,55,59,79],"new":[3,17],"problem":[4],"of":[5,54,94],"choosing":[6],"which":[7,20,58,72,118],"dense":[8,31,60,80,85,113],"retrieval":[9,32],"model":[10,38],"to":[11,77,97,122,131],"use":[12],"when":[13],"searching":[14],"on":[15,50,90,115],"a":[16,27,91,103],"collection":[18],"for":[19,71,117],"no":[21],"labels":[22,124],"are":[23,34,120],"available,":[24],"i.e.":[25],"in":[26,57,102],"zero-shot":[28],"setting.":[29],"Many":[30],"models":[33],"readily":[35],"available.":[36],"Each":[37],"however":[39],"is":[40,83],"characterized":[41],"by":[42,112],"very":[43],"differing":[44],"search":[45,100],"effectiveness":[46,101,109],"\u2013":[47],"not":[48,75,128,135],"just":[49],"test":[52],"portion":[53],"datasets":[56,70,116,132],"representations":[61],"have":[62,134],"been":[63,136],"learned":[64],"but,":[65],"importantly,":[66],"also":[67],"across":[68],"different":[69],"data":[73,96],"was":[74],"used":[76],"learn":[78],"representations.":[81],"This":[82],"because":[84],"retrievers":[86,114],"typically":[87],"require":[88],"training":[89],"large":[92],"amount":[93],"labeled":[95],"achieve":[98],"satisfactory":[99],"specific":[104],"dataset":[105],"or":[106],"domain.":[107],"Moreover,":[108],"gains":[110],"obtained":[111],"they":[119],"able":[121],"observe":[123],"during":[125,138],"training,":[126],"do":[127],"necessarily":[129],"generalise":[130],"that":[133],"observed":[137],"training.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}