{"id":"https://openalex.org/W7162529275","doi":"https://doi.org/10.48550/arxiv.2605.26947","title":"KZ-SafetyPrompts: A Kazakh Safety Evaluation Prompt Dataset for Large Language Models","display_name":"KZ-SafetyPrompts: A Kazakh Safety Evaluation Prompt Dataset for Large Language Models","publication_year":2026,"publication_date":"2026-05-26","ids":{"openalex":"https://openalex.org/W7162529275","doi":"https://doi.org/10.48550/arxiv.2605.26947"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.26947","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26947","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.2605.26947","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137168511","display_name":"Wajdi Zaghouani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zaghouani, Wajdi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130383440","display_name":"Shimaa Amer Ibrahim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ibrahim, Shimaa Amer","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137159071","display_name":"Aruzhan Muratbek","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Muratbek, Aruzhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137108030","display_name":"Olzhasbek Zhakenov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhakenov, Olzhasbek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137141243","display_name":"Adiya Akhmetzhanova","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akhmetzhanova, Adiya","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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.1949000060558319,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.1949000060558319,"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":0.1151999980211258,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.05249999836087227,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kazakh","display_name":"Kazakh","score":0.9854999780654907},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.38339999318122864},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.3427000045776367},{"id":"https://openalex.org/keywords/completeness","display_name":"Completeness (order theory)","score":0.3285999894142151},{"id":"https://openalex.org/keywords/text-messaging","display_name":"Text messaging","score":0.30379998683929443}],"concepts":[{"id":"https://openalex.org/C2781297163","wikidata":"https://www.wikidata.org/wiki/Q9252","display_name":"Kazakh","level":2,"score":0.9854999780654907},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5825999975204468},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.38339999318122864},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3824999928474426},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3427000045776367},{"id":"https://openalex.org/C17231256","wikidata":"https://www.wikidata.org/wiki/Q5156540","display_name":"Completeness (order theory)","level":2,"score":0.3285999894142151},{"id":"https://openalex.org/C3018949938","wikidata":"https://www.wikidata.org/wiki/Q17166101","display_name":"Text messaging","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2937000095844269},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.287200003862381},{"id":"https://openalex.org/C2987496018","wikidata":"https://www.wikidata.org/wiki/Q1860","display_name":"English language","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2596000134944916},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.26947","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26947","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.2605.26947","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26947","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/5","score":0.7559726238250732,"display_name":"Gender equality"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Kazakh":[0,18,56,145],"is":[1],"underrepresented":[2],"in":[3,55,73],"resources":[4],"for":[5,21,64],"evaluating":[6],"the":[7,90,111],"safety":[8,22,116,149],"behavior":[9],"of":[10,134],"large":[11],"language":[12],"models.":[13],"We":[14,88,108],"present":[15],"KZ-SafetyPrompts,":[16],"a":[17,74],"prompt":[19],"dataset":[20,49],"evaluation":[23,123],"across":[24,141],"eleven":[25],"categories":[26,112],"covering":[27],"common":[28],"risk":[29],"areas":[30],"such":[31],"as":[32,82],"self-harm,":[33],"violence,":[34],"child":[35,77],"exploitation,":[36],"sexual":[37],"content,":[38,40],"racist":[39],"radicalization,":[41],"and":[42,79,99,106],"regulated":[43],"goods":[44],"or":[45,76],"illegal":[46],"activities.":[47],"The":[48],"contains":[50],"5,717":[51],"prompts":[52,84,146],"written":[53],"natively":[54],"(Cyrillic),":[57],"organized":[58],"by":[59,153],"category,":[60],"with":[61,113,121,127],"English":[62],"translations":[63],"cross-lingual":[65],"analysis.":[66],"Prompts":[67],"resemble":[68],"realistic":[69],"user":[70],"queries,":[71],"often":[72],"teen":[75],"style,":[78],"are":[80],"phrased":[81],"intent":[83],"without":[85],"procedural":[86],"instructions.":[87],"document":[89],"writing":[91],"protocol,":[92],"labeling":[93],"procedures":[94],"(including":[95],"borderline-case":[96],"decision":[97],"rules),":[98],"quality-control":[100],"steps":[101],"(schema":[102],"standardization,":[103],"completeness":[104],"checks,":[105],"deduplication).":[107],"also":[109],"align":[110],"widely":[114],"used":[115],"taxonomies":[117],"to":[118,139],"support":[119],"integration":[120],"existing":[122],"pipelines.":[124],"Baseline":[125],"results":[126],"GPT-4o":[128],"show":[129],"an":[130],"overall":[131],"refusal":[132],"rate":[133],"28.2%,":[135],"varying":[136],"from":[137],"5.5%":[138],"53.8%":[140],"categories,":[142],"indicating":[143],"that":[144],"expose":[147],"category-specific":[148],"gaps":[150],"not":[151],"captured":[152],"English-only":[154],"evaluation.":[155]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-28T00:00:00"}
