{"id":"https://openalex.org/W7162667251","doi":"https://doi.org/10.48550/arxiv.2605.28098","title":"Examining Agents' Bias Amplification versus Suppression in Multi-Agent Systems","display_name":"Examining Agents' Bias Amplification versus Suppression in Multi-Agent Systems","publication_year":2026,"publication_date":"2026-05-27","ids":{"openalex":"https://openalex.org/W7162667251","doi":"https://doi.org/10.48550/arxiv.2605.28098"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.28098","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28098","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.2605.28098","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137269684","display_name":"Zejian Eric Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Zejian Eric","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137241730","display_name":"Zhongyi Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Zhongyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073048001","display_name":"Yuan Zhuang","orcid":"https://orcid.org/0000-0002-2964-3654"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhuang, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5006784495","display_name":"Paul Jen\u2010Hwa Hu","orcid":"https://orcid.org/0000-0002-4981-895X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Paul Jen-Hwa","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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.20829999446868896,"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"}},"topics":[{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.20829999446868896,"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":0.13519999384880066,"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"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.06040000170469284,"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/task","display_name":"Task (project management)","score":0.5394999980926514},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5163000226020813},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.3968999981880188},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.37059998512268066},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.36629998683929443},{"id":"https://openalex.org/keywords/criticality","display_name":"Criticality","score":0.36149999499320984}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5426999926567078},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5394999980926514},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5163000226020813},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.37059998512268066},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.36629998683929443},{"id":"https://openalex.org/C125611927","wikidata":"https://www.wikidata.org/wiki/Q17008131","display_name":"Criticality","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3538999855518341},{"id":"https://openalex.org/C40423286","wikidata":"https://www.wikidata.org/wiki/Q284172","display_name":"Selection bias","level":2,"score":0.3531000018119812},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.3255000114440918},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.31520000100135803},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C88629717","wikidata":"https://www.wikidata.org/wiki/Q17056323","display_name":"Information bias","level":3,"score":0.27079999446868896},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.28098","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28098","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.2605.28098","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28098","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":[{"score":0.7660990357398987,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-agent":[0],"systems":[1,20],"are":[2,111],"increasingly":[3],"deployed":[4],"to":[5,12,48,52,113],"support":[6],"various":[7],"tasks":[8],"where":[9],"agents":[10,51,99,110],"interact":[11],"achieve":[13],"individual":[14,50,127],"and":[15,25,41,83,91,145],"collective":[16],"objectives.":[17],"Although":[18],"these":[19],"can":[21,103],"enhance":[22],"task":[23],"performance":[24],"decision-making,":[26],"fairness":[27,137],"preservation":[28],"through":[29],"bias":[30,78,102,114,118],"reduction":[31],"remains":[32],"challenging.":[33],"This":[34],"study":[35],"examines":[36],"how":[37],"agent-level":[38],"biases":[39],"shift":[40],"impact":[42],"system-wide":[43,106,117],"fairness.":[44,107],"We":[45],"use":[46],"prompts":[47],"expose":[49],"group-favoring":[53],"bias,":[54],"then":[55],"assess":[56],"downstream":[57],"impacts":[58],"at":[59],"the":[60,65,116,122,126,134],"system":[61],"level.":[62],"To":[63],"quantify":[64],"impact,":[66],"we":[67,96],"propose":[68],"Favor":[69],"Bias":[70],"Strength":[71],"(FBS),":[72],"a":[73],"zero-centered":[74],"metric":[75],"that":[76,98],"decomposes":[77],"alteration":[79],"between":[80],"favored-group":[81],"uplift":[82],"disfavored-group":[84],"suppression.":[85],"Using":[86],"multiple":[87],"agent":[88],"designs,":[89],"benchmarks,":[90],"up-to-date":[92],"large":[93],"language":[94],"models,":[95],"show":[97],"endowed":[100],"with":[101],"substantially":[104],"affect":[105],"Interestingly,":[108],"when":[109],"exposed":[112],"uniformly,":[115],"elevates,":[119],"even":[120],"exceeding":[121],"additive":[123],"sum":[124],"of":[125,136],"agents'":[128],"biases.":[129],"The":[130],"empirical":[131,146],"evidence":[132],"underscores":[133],"criticality":[135],"in":[138],"multi-agent":[139],"systems,":[140],"which":[141],"warrants":[142],"further":[143],"analyses":[144],"tests.":[147]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-29T00:00:00"}
