{"id":"https://openalex.org/W4417100855","doi":"https://doi.org/10.48550/arxiv.2510.10978","title":"Does LLM Focus on the Right Words? Mitigating Context Bias in LLM-based Recommenders","display_name":"Does LLM Focus on the Right Words? Mitigating Context Bias in LLM-based Recommenders","publication_year":2025,"publication_date":"2025-10-13","ids":{"openalex":"https://openalex.org/W4417100855","doi":"https://doi.org/10.48550/arxiv.2510.10978"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2510.10978","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.10978","pdf_url":"https://arxiv.org/pdf/2510.10978","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.10978","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050239431","display_name":"Bohao Wang","orcid":"https://orcid.org/0009-0006-8264-3182","observed_orcids":["https://orcid.org/0009-0006-8264-3182"]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang, Bohao","raw_affiliation_strings":["Zhejiang University Hangzhou , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University Hangzhou , China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072238332","display_name":"Jiawei Chen","orcid":"https://orcid.org/0000-0001-7653-4998","observed_orcids":["https://orcid.org/0000-0001-7653-4998"]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen, Jiawei","raw_affiliation_strings":["Zhejiang University Hangzhou , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University Hangzhou , China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Liu, Feng","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Feng","raw_affiliation_strings":["OPPO Research Institute Shenzhen , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OPPO Research Institute Shenzhen , China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003963705","display_name":"Changwang Zhang","orcid":"https://orcid.org/0009-0004-4193-7833","observed_orcids":["https://orcid.org/0009-0004-4193-7833"]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang, Changwang","raw_affiliation_strings":["OPPO Research Institute Shenzhen , China","Zhejiang University Hangzhou , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OPPO Research Institute Shenzhen , China","institution_ids":[]},{"raw_affiliation_string":"Zhejiang University Hangzhou , China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384769","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-0481-5341","observed_orcids":["https://orcid.org/0000-0002-0481-5341","https://orcid.org/0000-0003-2787-8932","https://orcid.org/0000-0002-6750-5105"]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang, Jun","raw_affiliation_strings":["OPPO Research Institute Shenzhen , China","Zhejiang University Hangzhou , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OPPO Research Institute Shenzhen , China","institution_ids":[]},{"raw_affiliation_string":"Zhejiang University Hangzhou , China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037349726","display_name":"Canghong Jin","orcid":"https://orcid.org/0000-0002-9774-9688","observed_orcids":["https://orcid.org/0000-0002-9774-9688"]},"institutions":[{"id":"https://openalex.org/I4400573310","display_name":"Hangzhou City University","ror":"https://ror.org/01wck0s05","country_code":"CN","type":"education","lineage":["https://openalex.org/I4400573310"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin, Canghong","raw_affiliation_strings":["Hangzhou City University Hangzhou , China","OPPO Research Institute Shenzhen , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou City University Hangzhou , China","institution_ids":["https://openalex.org/I4400573310"]},{"raw_affiliation_string":"OPPO Research Institute Shenzhen , China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101139566","display_name":"Chun Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen, Chun","raw_affiliation_strings":["Zhejiang University Hangzhou , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University Hangzhou , China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100428564","display_name":"Can Wang","orcid":"https://orcid.org/0000-0002-0914-3994","observed_orcids":["https://orcid.org/0000-0002-0914-3994","https://orcid.org/0009-0005-8073-6011","https://orcid.org/0009-0001-1556-5181","https://orcid.org/0009-0008-7317-6791"]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang, Can","raw_affiliation_strings":["Zhejiang University Hangzhou , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University Hangzhou , China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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":1.0,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":9.999999747378752e-05,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/context-bias","display_name":"context bias","score":0.8159999847412109},{"id":"https://openalex.org/keywords/llm-based-recommender-systems","display_name":"LLM-based recommender systems","score":0.8669999837875366},{"id":"https://openalex.org/keywords/supervised-fine-tuning","display_name":"supervised fine-tuning","score":0.8709999918937683},{"id":"https://openalex.org/keywords/recommendation-fairness","display_name":"recommendation fairness","score":0.7699999809265137},{"id":"https://openalex.org/keywords/attentional-bias","display_name":"attentional bias","score":0.4020000100135803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7469000220298767},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6827999949455261},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6582000255584717},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6377999782562256},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.628600001335144},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6175000071525574},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5730999708175659},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.48539999127388},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.47530001401901245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4503999948501587},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4496999979019165},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4104999899864197},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.3880999982357025},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.3741999864578247},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33959999680519104},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.334199994802475},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2989000082015991},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.26989999413490295},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2619999945163727},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2590000033378601}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2510.10978","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.10978","pdf_url":"https://arxiv.org/pdf/2510.10978","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},{"id":"doi:10.48550/arxiv.2510.10978","doi":"https://doi.org/10.48550/arxiv.2510.10978","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.10978","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.10978","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.10978","pdf_url":"https://arxiv.org/pdf/2510.10978","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417100855.pdf","grobid_xml":"https://content.openalex.org/works/W4417100855.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4412394917","https://openalex.org/W7208828188","https://openalex.org/W7160691601","https://openalex.org/W4412376896","https://openalex.org/W4415036299","https://openalex.org/W7125777708","https://openalex.org/W4412377319","https://openalex.org/W7171963389","https://openalex.org/W7078700161","https://openalex.org/W4415346431"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs),":[3],"owing":[4],"to":[5,55,138,162],"their":[6,58],"extensive":[7],"open-domain":[8],"knowledge":[9],"and":[10,33,84,198],"semantic":[11],"reasoning":[12],"capabilities,":[13],"have":[14],"been":[15],"increasingly":[16],"integrated":[17],"into":[18],"recommender":[19],"systems":[20],"(RS).":[21],"However,":[22],"a":[23,66,121],"substantial":[24,186],"gap":[25],"remains":[26],"between":[27],"the":[28,34,74,155],"pre-training":[29],"objectives":[30],"of":[31,37,136,196],"LLMs":[32],"specific":[35],"requirements":[36],"recommendation":[38,53,102,189,201],"tasks.":[39],"To":[40,109],"address":[41,110],"this":[42,111],"gap,":[43],"supervised":[44],"fine-tuning":[45,123],"(SFT)":[46],"is":[47,205],"commonly":[48],"performed":[49],"on":[50,77,174],"specially":[51],"curated":[52],"datasets":[54,177],"further":[56],"enhance":[57],"predictive":[59],"ability.":[60],"Despite":[61],"its":[62],"success,":[63],"SFT":[64],"exhibits":[65],"critical":[67],"limitation:":[68],"it":[69],"induces":[70],"Context":[71],"Bias,":[72],"whereby":[73],"model":[75,128],"over-relies":[76],"auxiliary":[78,139,151,160],"tokens,":[79,86,152,166],"such":[80],"as":[81],"task":[82],"descriptions":[83],"prefix-generated":[85],"while":[87],"underutilizing":[88],"core":[89],"user":[90,164],"interaction":[91,165],"tokens":[92],"that":[93,125,179],"encode":[94],"user-specific":[95],"preferences.":[96],"This":[97],"bias":[98],"not":[99],"only":[100],"undermines":[101],"accuracy":[103,190],"but":[104],"also":[105],"raises":[106],"unfairness":[107],"concerns.":[108],"issue,":[112],"we":[113],"propose":[114],"Group":[115],"Distributionally":[116],"Robust":[117],"Optimization-based":[118],"Tuning":[119],"(GDRT),":[120],"novel":[122],"paradigm":[124],"enforces":[126],"consistent":[127],"performance":[129],"across":[130],"token":[131],"groups":[132],"with":[133,150],"varying":[134],"degrees":[135],"relevance":[137],"tokens.":[140],"By":[141],"adaptively":[142],"upweighting":[143],"underperforming":[144],"groups,":[145],"typically":[146],"those":[147],"weakly":[148],"correlated":[149],"GDRT":[153,180],"shifts":[154],"model's":[156],"attention":[157],"from":[158],"superficial":[159],"cues":[161],"informative":[163],"thereby":[167],"mitigating":[168],"context":[169,183],"bias.":[170],"Extensive":[171],"experiments":[172],"conducted":[173],"three":[175],"public":[176],"demonstrate":[178],"effectively":[181],"mitigates":[182],"bias,":[184],"yielding":[185],"improvements":[187],"in":[188],"(with":[191],"an":[192],"average":[193],"NDCG@10":[194],"gain":[195],"24.29%)":[197],"significantly":[199],"enhancing":[200],"fairness.":[202],"The":[203],"code":[204],"available":[206],"at":[207],"https://github.com/WANGBohaO-jpg/GDRT.":[208]},"counts_by_year":[],"updated_date":"2026-10-27T15:51:10.671819","created_date":"2025-10-15T00:00:00"}
