{"id":"https://openalex.org/W7164533376","doi":"https://doi.org/10.48550/arxiv.2606.13227","title":"PolyAlign: Conditional Human-Distribution Alignment","display_name":"PolyAlign: Conditional Human-Distribution Alignment","publication_year":2026,"publication_date":"2026-06-11","ids":{"openalex":"https://openalex.org/W7164533376","doi":"https://doi.org/10.48550/arxiv.2606.13227"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.13227","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13227","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.13227","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130599500","display_name":"L D M S S Teja","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Teja, L. D. M. S. Sai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136342684","display_name":"Ufaq Khan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Ufaq","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052661681","display_name":"Sathira Silva","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Silva, Sathira","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077880905","display_name":"\u5434\u6653","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138550118","display_name":"Muhammad Haris Khan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Muhammad Haris","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":0.23549999296665192,"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":0.23549999296665192,"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":0.2071000039577484,"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"}},{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.10260000079870224,"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/naturalness","display_name":"Naturalness","score":0.7240999937057495},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.5741999745368958},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.552299976348877},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.5110999941825867},{"id":"https://openalex.org/keywords/suite","display_name":"Suite","score":0.45809999108314514},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.362199991941452},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.34619998931884766},{"id":"https://openalex.org/keywords/global-optimization","display_name":"Global optimization","score":0.3440000116825104}],"concepts":[{"id":"https://openalex.org/C134537474","wikidata":"https://www.wikidata.org/wiki/Q17144832","display_name":"Naturalness","level":2,"score":0.7240999937057495},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6262999773025513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5878000259399414},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.5741999745368958},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.552299976348877},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.5110999941825867},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4449999928474426},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.362199991941452},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.34619998931884766},{"id":"https://openalex.org/C164752517","wikidata":"https://www.wikidata.org/wiki/Q5570875","display_name":"Global optimization","level":2,"score":0.3440000116825104},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C2777868144","wikidata":"https://www.wikidata.org/wiki/Q7239817","display_name":"Preference elicitation","level":3,"score":0.31949999928474426},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3059999942779541},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29280000925064087},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.13227","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13227","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.13227","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13227","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7462875843048096}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Post-training":[0],"methods":[1],"such":[2],"as":[3,45],"supervised":[4],"fine-tuning":[5],"(SFT)":[6],"and":[7,38,92,127,130,137],"preference":[8,111],"optimization":[9,100],"typically":[10],"align":[11],"language":[12],"models":[13,49],"toward":[14,156],"a":[15,64,71,121],"single":[16],"global":[17,153],"assistant":[18],"behavior.":[19],"While":[20],"effective":[21],"for":[22],"improving":[23],"average":[24],"helpfulness,":[25],"this":[26,43],"can":[27],"suppress":[28],"the":[29,52,58],"natural":[30],"variation":[31],"of":[32],"human":[33,53,82,118,160],"responses":[34],"across":[35,101],"languages,":[36],"tasks,":[37],"dialogue":[39],"settings.":[40],"We":[41,68],"study":[42],"problem":[44],"conditional":[46,135],"human-distribution":[47],"alignment:":[48],"should":[50,150],"match":[51],"response":[54,66,90,161],"distribution":[55],"appropriate":[56],"to":[57,116],"current":[59],"interaction":[60,78,88],"context,":[61],"rather":[62],"than":[63],"universal":[65],"style.":[67],"introduce":[69],"PolyAlign,":[70],"distribution-aware":[72],"alignment":[73,154,158],"framework":[74],"that":[75,148],"organizes":[76],"bilingual":[77,122],"data":[79],"into":[80],"bucket-specific":[81,117],"reference":[83],"distributions":[84],"defined":[85],"by":[86],"language,":[87],"track,":[89],"family,":[91],"length.":[93],"PolyAlign":[94,133],"combines":[95],"Bucket-Aware":[96],"SFT,":[97],"which":[98,109],"balances":[99],"heterogeneous":[102],"buckets,":[103],"with":[104,159],"Human-Distribution":[105],"Preference":[106],"Optimization":[107],"(HDPO),":[108],"regularizes":[110],"learning":[112],"using":[113],"critic-estimated":[114],"distance":[115],"support.":[119],"Across":[120],"evaluation":[123],"suite":[124],"covering":[125],"English":[126],"Chinese":[128],"single-":[129],"multi-turn":[131],"settings,":[132],"improves":[134],"naturalness":[136],"distributional":[138],"faithfulness":[139],"while":[140],"preserving":[141],"competitive":[142],"task":[143],"utility.":[144],"The":[145],"results":[146],"suggest":[147],"post-training":[149],"move":[151],"beyond":[152],"objectives":[155],"interaction-aware":[157],"distributions.":[162]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-13T00:00:00"}