{"id":"https://openalex.org/W4416016532","doi":"https://doi.org/10.1145/3746252.3761126","title":"LeadFairRec: LLM-enhanced Discriminative Counterfactual Debiasing for Two-sided Fairness in Recommendation","display_name":"LeadFairRec: LLM-enhanced Discriminative Counterfactual Debiasing for Two-sided Fairness in Recommendation","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W4416016532","doi":"https://doi.org/10.1145/3746252.3761126"},"language":null,"primary_location":{"id":"doi:10.1145/3746252.3761126","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761126","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","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/A5120301351","display_name":"Yimin Hou","orcid":"https://orcid.org/0009-0006-6485-9991"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yimin Hou","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China"],"raw_orcid":"https://orcid.org/0009-0006-6485-9991","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026995541","display_name":"Yue Kou","orcid":"https://orcid.org/0000-0002-5307-4893"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Kou","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China"],"raw_orcid":"https://orcid.org/0000-0002-5307-4893","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015251362","display_name":"Derong Shen","orcid":"https://orcid.org/0000-0003-0310-6372"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Derong Shen","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China"],"raw_orcid":"https://orcid.org/0000-0003-0310-6372","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024298278","display_name":"Xiangmin Zhou","orcid":"https://orcid.org/0000-0002-1302-818X"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xiangmin Zhou","raw_affiliation_strings":["School of Computing Technologies, RMIT University, Melbourne, Victoria, Australia"],"raw_orcid":"https://orcid.org/0000-0002-1302-818X","affiliations":[{"raw_affiliation_string":"School of Computing Technologies, RMIT University, Melbourne, Victoria, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101459858","display_name":"Dong Li","orcid":"https://orcid.org/0000-0003-3314-7124"},"institutions":[{"id":"https://openalex.org/I118803816","display_name":"Liaoning University","ror":"https://ror.org/03xpwj629","country_code":"CN","type":"education","lineage":["https://openalex.org/I118803816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Li","raw_affiliation_strings":["School of Information, Liaoning University, Shenyang, Liaoning, China"],"raw_orcid":"https://orcid.org/0000-0003-3314-7124","affiliations":[{"raw_affiliation_string":"School of Information, Liaoning University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I118803816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102979521","display_name":"Tiezheng Nie","orcid":"https://orcid.org/0000-0002-0166-1324"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiezheng Nie","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China"],"raw_orcid":"https://orcid.org/0000-0002-0166-1324","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ge Yu","orcid":"https://orcid.org/0009-0005-1729-226X"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Yu","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China"],"raw_orcid":"https://orcid.org/0009-0005-1729-226X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3589,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.9212741,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"867","last_page":"876"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.6412000060081482,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.6412000060081482,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.06300000101327896,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.04910000041127205,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/debiasing","display_name":"Debiasing","score":0.974399983882904},{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.9196000099182129},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.7185999751091003},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7001000046730042},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5874999761581421},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5651999711990356},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.48399999737739563},{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.45080000162124634}],"concepts":[{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.974399983882904},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9196000099182129},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.7185999751091003},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7001000046730042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6875},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5874999761581421},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5651999711990356},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.48399999737739563},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.45080000162124634},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.44699999690055847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42719998955726624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42399999499320984},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3366999924182892},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.31060001254081726},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27730000019073486},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2728999853134155},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.2612999975681305},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746252.3761126","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761126","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4520317839","display_name":null,"funder_award_id":"62472204, 62172082","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2001259128","https://openalex.org/W2155912844","https://openalex.org/W2604639157","https://openalex.org/W2971196067","https://openalex.org/W2997672513","https://openalex.org/W3008301325","https://openalex.org/W3035523484","https://openalex.org/W3045200674","https://openalex.org/W3097679710","https://openalex.org/W3155877950","https://openalex.org/W3156939347","https://openalex.org/W3208227120","https://openalex.org/W4200089543","https://openalex.org/W4283065823","https://openalex.org/W4284677642","https://openalex.org/W4297682444","https://openalex.org/W4384828614","https://openalex.org/W4385568387","https://openalex.org/W4391801184","https://openalex.org/W4393855546","https://openalex.org/W4396758712","https://openalex.org/W4396843911","https://openalex.org/W4400261185","https://openalex.org/W4401857110","https://openalex.org/W4403220393","https://openalex.org/W4403221136"],"related_works":[],"abstract_inverted_index":{"Fairness-aware":[0],"recommendation":[1],"has":[2],"emerged":[3],"as":[4],"a":[5,60,77],"pivotal":[6],"research":[7],"area":[8],"in":[9,32,53],"recent":[10],"years.":[11],"Current":[12],"fairness":[13,21,31,68],"studies":[14],"primarily":[15],"examine":[16],"two":[17],"independent":[18],"dimensions:":[19],"user-side":[20],"and":[22],"item-side":[23],"fairness.":[24],"However,":[25],"most":[26],"approaches":[27],"address":[28],"each":[29],"side's":[30],"isolation":[33],"while":[34,87],"neglecting":[35],"their":[36,71],"complex":[37],"interdependencies.":[38],"In":[39],"this":[40],"paper,":[41],"we":[42,57,75,93],"propose":[43,76,94],"an":[44,95],"LLM-Enhanced":[45],"DiscriminAtive":[46],"Counterfactual":[47],"Debiasing":[48],"Model":[49],"for":[50],"Two-sided":[51],"Fairness":[52],"Recommendation":[54],"(LeadFairRec).":[55],"Specifically,":[56],"first":[58],"design":[59],"two-sided":[61],"causal":[62,72,112],"graph":[63],"that":[64],"jointly":[65],"models":[66],"provider-customer":[67],"interactions":[69],"through":[70],"relationships.":[73],"Then":[74],"discriminative":[78],"counterfactual":[79,97],"debiasing":[80],"method,":[81],"which":[82],"effectively":[83],"removes":[84],"spurious":[85],"correlations":[86],"maintaining":[88],"true":[89],"user-item":[90],"interactions.":[91],"Finally,":[92],"LLM-enhanced":[96],"inference":[98],"method":[99],"to":[100],"derive":[101],"noise-resistant":[102],"user/item":[103],"representations":[104],"from":[105],"interaction":[106],"data,":[107],"enhancing":[108],"the":[109,118],"robustness":[110],"of":[111,121],"debiasing.":[113],"The":[114],"experimental":[115],"results":[116],"demonstrate":[117],"high":[119],"effectiveness":[120],"our":[122,127],"proposed":[123],"model.":[124],"We":[125],"provide":[126],"code":[128],"at":[129],"https://github.com/houyimin660/LeadFairRec.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-08T00:00:00"}
