{"id":"https://openalex.org/W7152651070","doi":"https://doi.org/10.48550/arxiv.2604.06210","title":"Distributional Open-Ended Evaluation of LLM Cultural Value Alignment Based on Value Codebook","display_name":"Distributional Open-Ended Evaluation of LLM Cultural Value Alignment Based on Value Codebook","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7152651070","doi":"https://doi.org/10.48550/arxiv.2604.06210"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.06210","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06210","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.06210","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133248429","display_name":"Jaehyeok Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lee, Jaehyeok","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133294839","display_name":"Xiaoyuan Yi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi, Xiaoyuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133277390","display_name":"Jing Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Jing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133312494","display_name":"Hyunjin Hwang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hwang, Hyunjin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133260632","display_name":"Roy Ka-Wei Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Roy Ka-Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133314371","display_name":"Xing Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Xing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133268541","display_name":"JinYeong Bak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bak, JinYeong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5133248429"],"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":0.46790000796318054,"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":0.46790000796318054,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.07940000295639038,"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/T10260","display_name":"Software Engineering Research","score":0.03920000046491623,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/codebook","display_name":"Codebook","score":0.6444000005722046},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6179999709129333},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5539000034332275},{"id":"https://openalex.org/keywords/dove","display_name":"Dove","score":0.5242000222206116},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4932999908924103},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4700999855995178},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4458000063896179}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.6444000005722046},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6179999709129333},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5539000034332275},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5430999994277954},{"id":"https://openalex.org/C109703566","wikidata":"https://www.wikidata.org/wiki/Q962709","display_name":"Dove","level":2,"score":0.5242000222206116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5153999924659729},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4932999908924103},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4700999855995178},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4458000063896179},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.373199999332428},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.373199999332428},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33970001339912415},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2953999936580658},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.06210","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06210","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":"doi:10.48550/arxiv.2604.06210","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06210","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7906191349029541,"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":{"As":[0],"LLMs":[1,106],"are":[2],"globally":[3],"deployed,":[4],"aligning":[5],"their":[6],"cultural":[7],"value":[8,32,83],"orientations":[9],"is":[10,90],"critical":[11],"for":[12],"safety":[13],"and":[14,41,100],"user":[15],"engagement.":[16],"However,":[17],"existing":[18],"benchmarks":[19],"face":[20],"the":[21],"Construct-Composition-Context":[22],"($C^3$)":[23],"challenge:":[24],"relying":[25],"on":[26],"discriminative,":[27],"multiple-choice":[28],"formats":[29],"that":[30,54,108],"probe":[31],"knowledge":[33],"rather":[34],"than":[35],"true":[36],"orientations,":[37],"overlook":[38],"subcultural":[39],"heterogeneity,":[40],"mismatch":[42],"with":[43,60,118,125],"real-world":[44],"open-ended":[45],"generation.":[46],"We":[47],"introduce":[48],"DOVE,":[49],"a":[50,65,72,81,115],"distributional":[51,98],"evaluation":[52],"framework":[53],"directly":[55],"compares":[56],"human-written":[57],"text":[58,79],"distributions":[59],"LLM-generated":[61],"outputs.":[62],"DOVE":[63,109],"utilizes":[64],"rate-distortion":[66],"variational":[67],"optimization":[68],"objective":[69],"to":[70,85],"construct":[71],"compact":[73],"value-codebook":[74],"from":[75],"10K":[76],"documents,":[77],"mapping":[78],"into":[80],"structured":[82],"space":[84],"filter":[86],"semantic":[87],"noise.":[88],"Alignment":[89],"measured":[91],"using":[92],"unbalanced":[93],"optimal":[94],"transport,":[95],"capturing":[96],"intra-cultural":[97],"structures":[99],"sub-group":[101],"diversity.":[102],"Experiments":[103],"across":[104],"12":[105],"show":[107],"achieves":[110],"superior":[111],"predictive":[112],"validity,":[113],"attaining":[114],"31.56%":[116],"correlation":[117],"downstream":[119],"tasks,":[120],"while":[121],"maintaining":[122],"high":[123],"reliability":[124],"as":[126,128],"few":[127],"500":[129],"samples":[130],"per":[131],"culture.":[132]},"counts_by_year":[],"updated_date":"2026-04-10T06:07:51.998497","created_date":"2026-04-10T00:00:00"}