{"id":"https://openalex.org/W7136838780","doi":"https://doi.org/10.48550/arxiv.2603.12271","title":"Diagnosing Retrieval Bias Under Multiple In-Context Knowledge Updates in Large Language Models","display_name":"Diagnosing Retrieval Bias Under Multiple In-Context Knowledge Updates in Large Language Models","publication_year":2026,"publication_date":"2026-02-18","ids":{"openalex":"https://openalex.org/W7136838780","doi":"https://doi.org/10.48550/arxiv.2603.12271"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.12271","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12271","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.12271","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129619641","display_name":"Boyu Qiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiao, Boyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129435890","display_name":"Sean Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Sean","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129594665","display_name":"Xian Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Xian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129520718","display_name":"Kun Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Kun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129628629","display_name":"Wei Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129632181","display_name":"Songlin Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Songlin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129419901","display_name":"Yunya Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yunya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T10028","display_name":"Topic Modeling","score":0.3598000109195709,"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/T10028","display_name":"Topic Modeling","score":0.3598000109195709,"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/T13629","display_name":"Text Readability and Simplification","score":0.05739999935030937,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.057100001722574234,"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/discriminative-model","display_name":"Discriminative model","score":0.7045999765396118},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5892999768257141},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.41370001435279846},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.36079999804496765},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.35120001435279846},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.3361000120639801}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.708299994468689},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7045999765396118},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5892999768257141},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5730999708175659},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5221999883651733},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36550000309944153},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.36079999804496765},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25920000672340393},{"id":"https://openalex.org/C2780665704","wikidata":"https://www.wikidata.org/wiki/Q959298","display_name":"Intervention (counseling)","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C49929091","wikidata":"https://www.wikidata.org/wiki/Q1930471","display_name":"General knowledge","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.12271","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12271","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.12271","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12271","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7212791442871094}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"LLMs":[0],"are":[1],"widely":[2],"used":[3],"in":[4,49,190,196],"knowledge-intensive":[5],"tasks":[6],"where":[7],"the":[8,45,53,64,90,110,165,182],"same":[9,54,91],"fact":[10,92],"may":[11],"be":[12],"revised":[13],"multiple":[14,31],"times":[15],"within":[16],"context.":[17],"Unlike":[18],"prior":[19],"work":[20],"focusing":[21],"on":[22,157],"one-shot":[23],"updates":[24,127,195],"or":[25],"single":[26],"conflicts,":[27],"multi-update":[28],"scenarios":[29],"contain":[30],"historically":[32],"valid":[33],"versions":[34],"that":[35,122,149],"compete":[36,69],"at":[37],"retrieval,":[38,71],"yet":[39],"remain":[40],"underexplored.":[41],"This":[42],"challenge":[43,189],"resembles":[44],"AB-AC":[46],"interference":[47],"paradigm":[48],"cognitive":[50],"psychology:":[51],"when":[52],"cue":[55,95],"A":[56],"is":[57],"successively":[58],"associated":[59],"with":[60,97],"B":[61],"and":[62,66,103,113,144,154,178,192],"C,":[63],"old":[65],"new":[67],"associations":[68],"during":[70],"leading":[72],"to":[73],"bias.":[74,183],"Inspired":[75],"by":[76],"this,":[77],"we":[78,120],"introduce":[79],"a":[80,94,98,187],"Dynamic":[81],"Knowledge":[82],"Instance":[83],"(DKI)":[84],"evaluation":[85],"framework,":[86],"modeling":[87],"multi-updates":[88],"of":[89,100,109,140],"as":[93,126],"paired":[96],"sequence":[99],"updated":[101],"values,":[102],"assess":[104],"models":[105],"via":[106],"endpoint":[107],"probing":[108],"earliest":[111],"(initial)":[112],"latest":[114,166],"(current)":[115],"states.":[116],"Across":[117],"diverse":[118],"LLMs,":[119],"observe":[121],"retrieval":[123],"bias":[124],"intensifies":[125],"increase,":[128],"earliest-state":[129],"accuracy":[130,135],"stays":[131],"high":[132],"while":[133],"latest-state":[134],"drops":[136],"substantially.":[137],"Diagnostic":[138],"analyses":[139],"attention,":[141],"hidden-state":[142],"similarity,":[143],"output":[145],"logits":[146],"further":[147],"reveal":[148,186],"these":[150],"signals":[151],"become":[152],"flatter":[153],"weakly":[155],"discriminative":[156],"errors,":[158],"providing":[159],"little":[160],"stable":[161],"basis":[162],"for":[163],"identifying":[164],"update.":[167],"Finally,":[168],"cognitively":[169],"inspired":[170],"heuristic":[171],"intervention":[172],"strategies":[173],"yield":[174],"only":[175],"modest":[176],"gains":[177],"do":[179],"not":[180],"eliminate":[181],"Our":[184],"results":[185],"persistent":[188],"tracking":[191],"following":[193],"knowledge":[194],"long":[197],"contexts.":[198]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-17T00:00:00"}
