{"id":"https://openalex.org/W2619206542","doi":"https://doi.org/10.1145/3077136.3080786","title":"IRGAN","display_name":"IRGAN","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2619206542","doi":"https://doi.org/10.1145/3077136.3080786","mag":"2619206542"},"language":"en","primary_location":{"id":"doi:10.1145/3077136.3080786","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3077136.3080786","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1705.10513","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jun Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["University College London, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lantao Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lantao Yu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Weinan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weinan Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yu Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Gong","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yinghui Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinghui Xu","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Benyou Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Benyou Wang","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Peng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Zhang","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":null,"display_name":"Dell Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I98259816","display_name":"Birkbeck, University of London","ror":"https://ror.org/02mb95055","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I98259816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dell Zhang","raw_affiliation_strings":["Birkbeck, University of London, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Birkbeck, University of London, London, United Kingdom","institution_ids":["https://openalex.org/I98259816"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":558,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"515","last_page":"524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14049","display_name":"Plant and Fungal Species Descriptions","score":0.9320999979972839,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T14049","display_name":"Plant and Fungal Species Descriptions","score":0.9320999979972839,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.947700023651123},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6402000188827515},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.632099986076355},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5758000016212463},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.4456999897956848},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.40790000557899475}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.947700023651123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6841999888420105},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6402000188827515},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.632099986076355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6273000240325928},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5758000016212463},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5257999897003174},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.4456999897956848},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.40790000557899475},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.39250001311302185},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2513999938964844}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3077136.3080786","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3077136.3080786","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1705.10513","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1705.10513","pdf_url":"https://arxiv.org/pdf/1705.10513","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1705.10513","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1705.10513","pdf_url":"https://arxiv.org/pdf/1705.10513","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1592871157","https://openalex.org/W1966443646","https://openalex.org/W2047221353","https://openalex.org/W2052088591","https://openalex.org/W2055007736","https://openalex.org/W2067802667","https://openalex.org/W2074694452","https://openalex.org/W2102035799","https://openalex.org/W2108862644","https://openalex.org/W2120391124","https://openalex.org/W2143331230","https://openalex.org/W2169347997","https://openalex.org/W2251202616","https://openalex.org/W2295739661","https://openalex.org/W2512971201","https://openalex.org/W2539247542","https://openalex.org/W2964154091","https://openalex.org/W2964341035","https://openalex.org/W2988119488","https://openalex.org/W4206765718","https://openalex.org/W4233135949"],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"provides":[2,65],"a":[3,24,35,40,173,202],"unified":[4,126],"account":[5],"of":[6,9,130,133,204],"two":[7,120],"schools":[8,132],"thinking":[10],"in":[11,106,201],"information":[12],"retrieval":[13,17,29],"modelling:":[14],"the":[15,27,53,69,74,81,84,87,95,103,116,125,136,142,148,151,156,163,168],"generative":[16,70,88,137,169],"focusing":[18,30],"on":[19,31,191,196],"predicting":[20,32],"relevant":[21],"documents":[22,79,146],"given":[23,34,80],"query,":[25],"and":[26,62,154,194,211],"discriminative":[28,54,97,104,152,157],"relevancy":[33],"query-document":[36],"pair.":[37],"We":[38],"propose":[39],"game":[41,44],"theoretical":[42],"minimax":[43],"to":[45,57,67,94,140,161,171],"iteratively":[46],"optimise":[47],"both":[48,131],"models.":[49],"On":[50,83],"one":[51],"hand,":[52,86],"model,":[55,89,98,153],"aiming":[56],"mine":[58],"signals":[59,149],"from":[60,150],"labelled":[61],"unlabelled":[63,164],"data,":[64],"guidance":[66],"train":[68],"model":[71,105,138,158,170],"towards":[72],"fitting":[73],"underlying":[75],"relevance":[76,143],"distribution":[77,144],"over":[78,145,198],"query.":[82],"other":[85],"acting":[90],"as":[91,187,189],"an":[92,107],"attacker":[93],"current":[96],"generates":[99],"difficult":[100],"examples":[101],"for":[102,176],"adversarial":[108],"way":[109],"by":[110,167],"minimising":[111],"its":[112],"discrimination":[113],"objective.":[114],"With":[115],"competition":[117],"between":[118],"these":[119],"models,":[121],"we":[122],"show":[123],"that":[124],"framework":[127],"takes":[128],"advantage":[129],"thinking:":[134],"(i)":[135],"learns":[139],"fit":[141],"via":[147],"(ii)":[155],"is":[159],"able":[160],"exploit":[162],"data":[165],"selected":[166],"achieve":[172],"better":[174],"estimation":[175],"document":[177],"ranking.":[178],"Our":[179],"experimental":[180],"results":[181],"have":[182],"demonstrated":[183],"significant":[184],"performance":[185],"gains":[186],"much":[188],"23.96%":[190],"[email":[192],"protected]":[193],"15.50%":[195],"MAP":[197],"strong":[199],"baselines":[200],"variety":[203],"applications":[205],"including":[206],"web":[207],"search,":[208],"item":[209],"recommendation,":[210],"question":[212],"answering.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":23},{"year":2025,"cited_by_count":51},{"year":2024,"cited_by_count":61},{"year":2023,"cited_by_count":55},{"year":2022,"cited_by_count":61},{"year":2021,"cited_by_count":79},{"year":2020,"cited_by_count":84},{"year":2019,"cited_by_count":88},{"year":2018,"cited_by_count":54},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-18T07:39:51.176621","created_date":"2017-06-05T00:00:00"}
