{"id":"https://openalex.org/W7159570278","doi":"https://doi.org/10.48550/arxiv.2604.26960","title":"LLM Biases","display_name":"LLM Biases","publication_year":2026,"publication_date":"2026-04-07","ids":{"openalex":"https://openalex.org/W7159570278","doi":"https://doi.org/10.48550/arxiv.2604.26960"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.26960","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26960","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.26960","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134976768","display_name":"Jinhui Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Jinhui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134969067","display_name":"Ming Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Ming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134963277","display_name":"Xilin Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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/T12607","display_name":"Personal Information Management and User Behavior","score":0.24779999256134033,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12607","display_name":"Personal Information Management and User Behavior","score":0.24779999256134033,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.06499999761581421,"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":0.06040000170469284,"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/popularity","display_name":"Popularity","score":0.5529999732971191},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5282999873161316},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5218999981880188},{"id":"https://openalex.org/keywords/ask-price","display_name":"Ask price","score":0.4846000075340271},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4805999994277954},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4359000027179718},{"id":"https://openalex.org/keywords/confirmation-bias","display_name":"Confirmation bias","score":0.40869998931884766},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.39800000190734863}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6110000014305115},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.5529999732971191},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5282999873161316},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5218999981880188},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.4846000075340271},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4805999994277954},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4359000027179718},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.41519999504089355},{"id":"https://openalex.org/C79585631","wikidata":"https://www.wikidata.org/wiki/Q431498","display_name":"Confirmation bias","level":2,"score":0.40869998931884766},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.39800000190734863},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33009999990463257},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3043999969959259},{"id":"https://openalex.org/C2779426996","wikidata":"https://www.wikidata.org/wiki/Q18389128","display_name":"Echo (communications protocol)","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2906000018119812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2856000065803528},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2671999931335449},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.26570001244544983},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.258899986743927}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.26960","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26960","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.26960","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26960","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Transformer-based":[0],"agentic":[1],"AI":[2,183],"is":[3,31,81,237],"rapidly":[4],"being":[5],"deployed":[6],"on":[7,89,165,188],"major":[8],"platforms":[9,186],"to":[10,138,238,246],"help":[11],"users":[12,180],"shop,":[13],"watch,":[14],"and":[15,120,141,185,197,230,245,249],"navigate":[16],"content":[17],"with":[18],"less":[19,36],"effort.":[20],"While":[21],"these":[22,240],"systems":[23],"can":[24,56,131,160,193,200],"deliver":[25],"impressive":[26],"performance,":[27],"a":[28,43,68,166],"key":[29],"concern":[30],"whether":[32,48],"they":[33,39],"may":[34,210,226],"be":[35,132,212],"reliable":[37],"than":[38,254],"appear.":[40],"We":[41,63],"ask":[42],"simple":[44],"but":[45,116],"fundamental":[46],"question:":[47],"the":[49,77,85,91,158,234],"mechanisms":[50],"that":[51,209,223,256],"make":[52],"transformer-based":[53,72],"agents":[54],"effective":[55],"also":[57],"induce":[58],"systematic":[59],"biases":[60],"or":[61],"distortions?":[62],"study":[64],"this":[65],"question":[66],"through":[67],"theoretical":[69],"analysis":[70,204],"of":[71,151,169],"generative":[73],"recommenders,":[74],"in":[75,129,214],"which":[76],"next":[78],"user":[79,86,152],"interaction":[80],"generated":[82],"sequentially":[83],"from":[84],"history.":[87],"Focusing":[88],"how":[90],"model":[92,159],"allocates":[93],"attention":[94],"across":[95],"historical":[96],"evidence,":[97],"we":[98],"identify":[99],"four":[100,219],"bias":[101,220],"channels:":[102],"(i)":[103],"Positional":[104],"bias:":[105,147,178],"stronger":[106],"positional":[107],"encoding":[108],"shifts":[109],"influence":[110],"toward":[111],"recent":[112],"history,":[113],"improving":[114],"responsiveness":[115],"potentially":[117],"reducing":[118],"stability":[119],"long-term":[121],"diversity;":[122],"(ii)":[123],"Popularity":[124],"amplification:":[125],"small":[126,167],"frequency":[127],"differences":[128],"data":[130,177],"magnified":[133],"into":[134],"disproportionate":[135],"exposure,":[136],"contributing":[137],"Matthew":[139],"effects":[140],"echo":[142],"chambers;":[143],"(iii)":[144],"Latent":[145],"driver":[146],"when":[148,179],"important":[149],"drivers":[150],"choices":[153],"are":[154],"not":[155,211],"directly":[156],"observed,":[157],"place":[161],"overly":[162],"concentrated":[163],"weight":[164],"subset":[168],"past":[170],"events,":[171],"creating":[172],"overconfident":[173],"attributions.":[174],"(iv)":[175],"Synthetic":[176],"increasingly":[181],"follow":[182],"suggestions":[184],"retrain":[187],"model-shaped":[189],"synthetic":[190],"logs,":[191],"outputs":[192],"concentrate":[194],"over":[195,251],"time,":[196,252],"long-tail":[198],"alternatives":[199],"disappear":[201],"first.":[202],"Our":[203],"highlights":[205],"mechanism-level":[206],"reliability":[207],"risks":[208],"visible":[213],"offline":[215],"performance":[216,257],"metrics.":[217],"The":[218],"channels":[221],"indicate":[222],"large-scale":[224],"deployment":[225],"systematically":[227],"distort":[228],"exposure":[229],"choice.":[231],"For":[232],"managers,":[233],"immediate":[235],"implication":[236],"treat":[239],"as":[241],"operational":[242],"risk":[243],"factors":[244],"monitor":[247],"concentration":[248],"drift":[250],"rather":[253],"assuming":[255],"gains":[258],"alone":[259],"guarantee":[260],"reliability.":[261]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-02T00:00:00"}
