{"id":"https://openalex.org/W7128515446","doi":"https://doi.org/10.48550/arxiv.2602.08259","title":"A Statistical Framework for Alignment with Biased AI Feedback","display_name":"A Statistical Framework for Alignment with Biased AI Feedback","publication_year":2026,"publication_date":"2026-02-09","ids":{"openalex":"https://openalex.org/W7128515446","doi":"https://doi.org/10.48550/arxiv.2602.08259"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.08259","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125584292","display_name":"Xintao Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xia, Xintao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020462099","display_name":"Zhiqiu Xia","orcid":"https://orcid.org/0000-0002-1430-8992"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Zhiqiu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125519186","display_name":"Linjun Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Linjun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5069961927","display_name":"Zhanrui Cai","orcid":"https://orcid.org/0000-0003-3359-9446"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Zhanrui","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5125584292"],"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.5281000137329102,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.5281000137329102,"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/T10028","display_name":"Topic Modeling","score":0.20250000059604645,"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/T12031","display_name":"Speech and dialogue systems","score":0.026900000870227814,"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/preference","display_name":"Preference","score":0.6078000068664551},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5727999806404114},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.5703999996185303},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.3605000078678131},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.3237999975681305}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7128999829292297},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.6078000068664551},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5727999806404114},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.5703999996185303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5249999761581421},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4375},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.3605000078678131},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25519999861717224}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.08259","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.08259","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08259","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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.08259","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modern":[0],"alignment":[1,37,142],"pipelines":[2],"are":[3],"increasingly":[4],"replacing":[5],"expensive":[6],"human":[7,27,50,84],"preference":[8,85],"labels":[9,19],"with":[10,61],"evaluations":[11],"from":[12],"large":[13],"language":[14],"models":[15],"(LLM-as-Judge).":[16],"However,":[17],"AI":[18],"can":[20],"be":[21],"systematically":[22],"biased":[23],"compared":[24],"to":[25,68,148],"high-quality":[26],"feedback":[28,51],"datasets.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33],"develop":[34],"two":[35],"debiased":[36],"methods":[38,139],"within":[39],"a":[40,62,89,102,115],"general":[41],"framework":[42],"that":[43,120,136,149],"accommodates":[44],"heterogeneous":[45],"prompt-response":[46],"distributions":[47],"and":[48,65,104,132,144],"external":[49],"sources.":[52],"Debiased":[53,77],"Direct":[54],"Preference":[55,79],"Optimization":[56,80],"(DDPO)":[57],"augments":[58],"standard":[59],"DPO":[60],"residual-based":[63],"correction":[64],"density-ratio":[66],"reweighting":[67],"mitigate":[69],"systematic":[70],"bias,":[71],"while":[72],"retaining":[73],"DPO's":[74],"computational":[75],"efficiency.":[76],"Identity":[78],"(DIPO)":[81],"directly":[82],"estimates":[83],"probabilities":[86],"without":[87],"imposing":[88],"parametric":[90],"reward":[91],"model.":[92],"We":[93],"provide":[94],"theoretical":[95],"guarantees":[96],"for":[97,108],"both":[98],"methods:":[99],"DDPO":[100],"offers":[101],"practical":[103],"computationally":[105],"efficient":[106],"solution":[107],"large-scale":[109],"alignment,":[110],"whereas":[111],"DIPO":[112],"serves":[113],"as":[114],"robust,":[116],"statistically":[117],"optimal":[118],"alternative":[119],"attains":[121],"the":[122,137],"semiparametric":[123],"efficiency":[124,143],"bound.":[125],"Empirical":[126],"studies":[127],"on":[128,154],"sentiment":[129],"generation,":[130],"summarization,":[131],"single-turn":[133],"dialogue":[134],"demonstrate":[135],"proposed":[138],"substantially":[140],"improve":[141],"recover":[145],"performance":[146],"close":[147],"of":[150],"an":[151],"oracle":[152],"trained":[153],"fully":[155],"human-labeled":[156],"data.":[157]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-11T00:00:00"}