{"id":"https://openalex.org/W4394947904","doi":"https://doi.org/10.1145/3637528.3671458","title":"Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era","display_name":"Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4394947904","doi":"https://doi.org/10.1145/3637528.3671458"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671458","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3637528.3671458","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671458","source":null,"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 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671458","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075518954","display_name":"Sunhao Dai","orcid":"https://orcid.org/0009-0002-7549-0860"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sunhao Dai","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385709","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0002-3070-9358"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Xu","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101749108","display_name":"Shicheng Xu","orcid":"https://orcid.org/0000-0001-7157-3410"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shicheng Xu","raw_affiliation_strings":["CAS Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004759804","display_name":"Liang Pang","orcid":"https://orcid.org/0000-0003-1161-8546"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Pang","raw_affiliation_strings":["CAS Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021124418","display_name":"Zhenhua Dong","orcid":"https://orcid.org/0000-0002-2231-4663"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Dong","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020766468","display_name":"Jun Xu","orcid":"https://orcid.org/0000-0001-7170-111X"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Xu","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5075518954"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":31.2127,"has_fulltext":true,"cited_by_count":92,"citation_normalized_percentile":{"value":0.99793879,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"6437","last_page":"6447"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.8942999839782715,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.8942999839782715,"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":0.8422999978065491,"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/information-retrieval","display_name":"Information retrieval","score":0.5009019374847412},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46944376826286316},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.38109809160232544}],"concepts":[{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5009019374847412},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46944376826286316},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38109809160232544}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3637528.3671458","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3637528.3671458","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671458","source":null,"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 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2404.11457","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.11457","pdf_url":"https://arxiv.org/pdf/2404.11457","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3637528.3671458","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3637528.3671458","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671458","source":null,"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 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6058138561","display_name":null,"funder_award_id":", No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6620384876","display_name":null,"funder_award_id":"62377044","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7033253288","display_name":null,"funder_award_id":"Grants","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8394619546","display_name":null,"funder_award_id":"2023111","funder_id":"https://openalex.org/F4320322847","funder_display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences"},{"id":"https://openalex.org/G8955107213","display_name":null,"funder_award_id":"Major","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G986537704","display_name":null,"funder_award_id":"62276248","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/F4320322499","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92"},{"id":"https://openalex.org/F4320322847","display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences","ror":"https://ror.org/031141b54"},{"id":"https://openalex.org/F4320335892","display_name":"Youth Innovation Promotion Association","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4394947904.pdf"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2791170418","https://openalex.org/W2809770202","https://openalex.org/W2810397803","https://openalex.org/W2963908320","https://openalex.org/W3004493409","https://openalex.org/W3092103025","https://openalex.org/W3099814932","https://openalex.org/W3101767999","https://openalex.org/W3133702157","https://openalex.org/W3156939347","https://openalex.org/W3171676064","https://openalex.org/W3172253407","https://openalex.org/W3173610337","https://openalex.org/W3184144760","https://openalex.org/W4220993274","https://openalex.org/W4256256957","https://openalex.org/W4287854553","https://openalex.org/W4321488452","https://openalex.org/W4367047007","https://openalex.org/W4385570777","https://openalex.org/W4385572266","https://openalex.org/W4385573668","https://openalex.org/W4386200967","https://openalex.org/W4386566641","https://openalex.org/W4386730022","https://openalex.org/W4388778348","https://openalex.org/W4389519254","https://openalex.org/W4389519585","https://openalex.org/W4389519598","https://openalex.org/W4389519856","https://openalex.org/W4389524193","https://openalex.org/W4391689563","https://openalex.org/W4392846385","https://openalex.org/W4396736140","https://openalex.org/W4396832250","https://openalex.org/W4401042906","https://openalex.org/W4401043313","https://openalex.org/W4401224724","https://openalex.org/W4402683999","https://openalex.org/W4404534210"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"With":[0],"the":[1,45,71,102,138,169,197],"rapid":[2],"advancements":[3],"of":[4,38,56,73,113,183],"large":[5],"language":[6],"models":[7],"(LLMs),":[8],"information":[9,46],"retrieval":[10],"(IR)":[11],"systems,":[12,19],"such":[13],"as":[14,82],"search":[15],"engines":[16],"and":[17,40,61,64,79,105,123,132,141,152,157,166,172,177,180,200],"recommender":[18],"have":[20],"undergone":[21],"a":[22,53,87,193],"significant":[23],"paradigm":[24],"shift.":[25],"This":[26],"evolution,":[27],"while":[28],"heralding":[29],"new":[30],"opportunities,":[31],"introduces":[32],"emerging":[33,60],"challenges,":[34],"particularly":[35],"in":[36,67,168,185,202],"terms":[37],"biases":[39],"unfairness,":[41],"which":[42],"may":[43],"threaten":[44],"ecosystem.":[47],"In":[48,126],"this":[49,186,203],"paper,":[50],"we":[51,98,129,150],"present":[52],"comprehensive":[54],"survey":[55],"existing":[57],"works":[58],"on":[59,137],"pressing":[62],"bias":[63,78,104,179],"unfairness":[65,80,106,181],"issues":[66,81,107,182],"IR":[68,117,170,184],"systems":[69],"when":[70],"integration":[72,115],"LLMs.":[74],"We":[75,189],"first":[76],"unify":[77],"distribution":[83,95],"mismatch":[84],"problems,":[85],"providing":[86],"groundwork":[88],"for":[89,159,196],"categorizing":[90],"various":[91],"mitigation":[92,143],"strategies":[93,144],"through":[94],"alignment.":[96],"Subsequently,":[97],"systematically":[99],"delve":[100],"into":[101,116],"specific":[103],"arising":[108],"from":[109],"three":[110],"critical":[111],"stages":[112],"LLMs":[114],"systems:":[118],"data":[119],"collection,":[120],"model":[121],"development,":[122],"result":[124],"evaluation.":[125],"doing":[127],"so,":[128],"meticulously":[130],"review":[131],"analyze":[133],"recent":[134],"literature,":[135],"focusing":[136],"definitions,":[139],"characteristics,":[140],"corresponding":[142],"associated":[145],"with":[146],"these":[147],"issues.":[148],"Finally,":[149],"identify":[151],"highlight":[153],"some":[154],"open":[155],"problems":[156],"challenges":[158],"future":[160],"work,":[161],"aiming":[162],"to":[163,174],"inspire":[164],"researchers":[165],"stakeholders":[167],"field":[171],"beyond":[173],"better":[175],"understand":[176],"mitigate":[178],"LLM":[187],"era.":[188],"also":[190],"consistently":[191],"maintain":[192],"GitHub":[194],"repository":[195],"relevant":[198],"papers":[199],"resources":[201],"rising":[204],"direction":[205],"at":[206],"https://github.com/KID-22/LLM-IR-Bias-Fairness-Survey.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":15},{"year":2025,"cited_by_count":74},{"year":2024,"cited_by_count":3}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2024-04-19T00:00:00"}