{"id":"https://openalex.org/W7160271656","doi":"https://doi.org/10.48550/arxiv.2605.02435","title":"Generalized Distributional Alignment Games for Unbiased Answer-Level Fine-Tuning","display_name":"Generalized Distributional Alignment Games for Unbiased Answer-Level Fine-Tuning","publication_year":2026,"publication_date":"2026-05-04","ids":{"openalex":"https://openalex.org/W7160271656","doi":"https://doi.org/10.48550/arxiv.2605.02435"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.02435","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.02435","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.2605.02435","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058849006","display_name":"Mehryar Mohri","orcid":"https://orcid.org/0000-0002-3987-9847"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohri, Mehryar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135404436","display_name":"Jon Schneider","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schneider, Jon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135336614","display_name":"Yutao Zhong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhong, Yutao","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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.2379000037908554,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.2379000037908554,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.10589999705553055,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.06719999760389328,"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/minimax","display_name":"Minimax","score":0.7355999946594238},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5584999918937683},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.5472999811172485},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5239999890327454},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.515999972820282},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4431000053882599},{"id":"https://openalex.org/keywords/game-theory","display_name":"Game theory","score":0.3849000036716461}],"concepts":[{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.7355999946594238},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5584999918937683},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.5472999811172485},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5462999939918518},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5239999890327454},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5203999876976013},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.515999972820282},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4431000053882599},{"id":"https://openalex.org/C177142836","wikidata":"https://www.wikidata.org/wiki/Q44455","display_name":"Game theory","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.37610000371932983},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3481000065803528},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3375000059604645},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3310000002384186},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.2842999994754791},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.2784000039100647}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.02435","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.02435","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.2605.02435","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.02435","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","score":0.5314874053001404,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"Distributional":[1],"Alignment":[2],"Game":[3],"framework":[4],"provides":[5],"a":[6,29,63,95,128],"powerful":[7],"variational":[8],"perspective":[9],"on":[10,21],"Answer-Level":[11],"Fine-Tuning":[12],"(ALFT).":[13],"However,":[14],"standard":[15],"algorithms":[16],"for":[17,62,81],"these":[18,123],"games":[19],"rely":[20],"estimating":[22],"logarithmic":[23],"rewards":[24],"from":[25],"small":[26],"batches,":[27],"introducing":[28],"systematic":[30],"bias":[31,149],"due":[32],"to":[33,56,126,157],"Jensen's":[34],"inequality":[35],"that":[36,61,101,138],"can":[37,71],"destabilize":[38],"training.":[39],"In":[40],"this":[41,46],"paper,":[42],"we":[43,51,70,93,114,121],"systematically":[44,140],"resolve":[45],"structural":[47],"estimation":[48],"bias.":[49],"First,":[50],"generalize":[52],"the":[53,82,106,117],"alignment":[54],"game":[55,86,154],"arbitrary":[57],"Bregman":[58],"divergences,":[59],"showing":[60],"family":[64],"of":[65,111],"geometries":[66],"inducing":[67],"polynomial":[68,99],"rewards,":[69],"construct":[72],"provably":[73,103,152],"exact":[74,89],"and":[75,160],"unbiased":[76],"estimators":[77],"using":[78],"U-statistics.":[79],"Second,":[80],"canonical":[83],"KL":[84],"divergence":[85],"where":[87],"an":[88],"solution":[90],"is":[91,102],"impossible,":[92],"derive":[94],"globally":[96],"robust":[97],"minimax":[98],"estimator":[100],"optimal,":[104],"achieving":[105],"fundamental":[107],"statistical":[108],"error":[109],"limit":[110],"$\u0398(1/K^2)$,":[112],"which":[113],"establish":[115],"via":[116],"Ditzian-Totik":[118],"theorem.":[119],"Finally,":[120],"synthesize":[122],"two":[124],"approaches":[125],"propose":[127],"novel":[129],"Variance-Optimal":[130],"Augmented":[131],"Polynomial":[132],"Optimization":[133],"Program":[134],"(AQP)":[135],"Estimator,":[136],"proving":[137],"by":[139],"reducing":[141],"variance,":[142],"our":[143],"method":[144],"achieves":[145],"not":[146],"only":[147],"optimal":[148],"but":[150],"also":[151],"accelerated":[153],"convergence,":[155],"leading":[156],"more":[158],"efficient":[159],"stable":[161],"training":[162],"with":[163],"zero":[164],"online":[165],"computational":[166],"overhead.":[167]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-06T00:00:00"}