{"id":"https://openalex.org/W7108318605","doi":"https://doi.org/10.1145/3767695.3769514","title":"Developing a Framework for Auditing Large Language Models using Human-in-the-loop","display_name":"Developing a Framework for Auditing Large Language Models using Human-in-the-loop","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W7108318605","doi":"https://doi.org/10.1145/3767695.3769514"},"language":null,"primary_location":{"id":"doi:10.1145/3767695.3769514","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767695.3769514","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3767695.3769514","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Maryam Amirizaniani","orcid":"https://orcid.org/0000-0002-6142-0637"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maryam Amirizaniani","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"raw_orcid":"https://orcid.org/0000-0002-6142-0637","affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Adrian Lavergne","orcid":"https://orcid.org/0009-0007-4790-4292"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adrian Lavergne","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"raw_orcid":"https://orcid.org/0009-0007-4790-4292","affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Elizabeth Snell Okada","orcid":"https://orcid.org/0009-0003-1436-8084"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elizabeth Snell Okada","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"raw_orcid":"https://orcid.org/0009-0003-1436-8084","affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Aman Chadha","orcid":"https://orcid.org/0000-0001-6621-9003"},"institutions":[{"id":"https://openalex.org/I1743320","display_name":"Palo Alto University","ror":"https://ror.org/04f812k67","country_code":"US","type":"education","lineage":["https://openalex.org/I1743320"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aman Chadha","raw_affiliation_strings":["Stanford University, Palo Alto, CA, USA and Amazon AI, Palo Alto, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-6621-9003","affiliations":[{"raw_affiliation_string":"Stanford University, Palo Alto, CA, USA and Amazon AI, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I1743320"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tanya Roosta","orcid":"https://orcid.org/0009-0003-1235-3006"},"institutions":[{"id":"https://openalex.org/I4210136029","display_name":"Saratoga Hospital","ror":"https://ror.org/048j1wp71","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210136029"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tanya Roosta","raw_affiliation_strings":["UC Berkeley, Saratoga, CA, USA and Amazon, Saratoga, CA, USA"],"raw_orcid":"https://orcid.org/0009-0003-1235-3006","affiliations":[{"raw_affiliation_string":"UC Berkeley, Saratoga, CA, USA and Amazon, Saratoga, CA, USA","institution_ids":["https://openalex.org/I4210136029"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chirag Shah","orcid":"https://orcid.org/0000-0002-3797-4293"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chirag Shah","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3797-4293","affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"64","last_page":"74"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.18690000474452972,"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":0.18690000474452972,"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":0.18369999527931213,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.050200000405311584,"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/audit","display_name":"Audit","score":0.8145999908447266},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.7638000249862671},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.734000027179718},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.6891999840736389},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.48420000076293945},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4505000114440918}],"concepts":[{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.8145999908447266},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.7638000249862671},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.734000027179718},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.6891999840736389},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6796000003814697},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.489300012588501},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.48420000076293945},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4505000114440918},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42739999294281006},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4165000021457672},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.36640000343322754},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3409999907016754},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.31380000710487366},{"id":"https://openalex.org/C197947376","wikidata":"https://www.wikidata.org/wiki/Q5155608","display_name":"Comparability","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.2757999897003174},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27549999952316284},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.26600000262260437},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3767695.3769514","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767695.3769514","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3767695.3769514","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767695.3769514","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.43173378705978394}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2141766660","https://openalex.org/W3118813946","https://openalex.org/W3185341429","https://openalex.org/W3207316473","https://openalex.org/W4285113702","https://openalex.org/W4285231210","https://openalex.org/W4309674289","https://openalex.org/W4321207578","https://openalex.org/W4381572755","https://openalex.org/W4385565387","https://openalex.org/W4385571301","https://openalex.org/W4386246835","https://openalex.org/W4386942825","https://openalex.org/W4387848774","https://openalex.org/W4389518833","https://openalex.org/W4389519460","https://openalex.org/W4389523621","https://openalex.org/W4392182430","https://openalex.org/W4392376454","https://openalex.org/W4393212973","https://openalex.org/W4396758529","https://openalex.org/W4396832834","https://openalex.org/W4396833706","https://openalex.org/W4403577490","https://openalex.org/W4404781001","https://openalex.org/W4409720313","https://openalex.org/W4409749538","https://openalex.org/W4410217873","https://openalex.org/W4411050504"],"related_works":[],"abstract_inverted_index":{"As":[0],"LLMs":[1,16,205],"become":[2],"more":[3],"widely":[4],"adopted,":[5],"detecting":[6],"inconsistencies":[7,19],"like":[8],"bias":[9],"and":[10,105,151,191,195,231],"hallucination":[11],"is":[12,20],"increasingly":[13],"important.":[14],"Auditing":[15],"for":[17,28,138,223],"these":[18,47,111,170],"crucial":[21],"but":[22],"often":[23],"challenging.":[24],"An":[25],"effective":[26],"method":[27],"auditing":[29,199],"an":[30,128],"LLM":[31,129,161,234],"involves":[32],"using":[33,164],"variations":[34],"of":[35,84,142,149,197,218,233],"the":[36,53,59,82,85,101,136,176,193,198,229],"same":[37],"question,":[38],"referred":[39],"to":[40,46,80,94,107,126,174],"as":[41],"probes,":[42],"where":[43],"consistent":[44],"responses":[45,54],"probes":[48,69,163,171],"are":[49,172],"expected.":[50],"Deviations":[51],"in":[52,58,130,155,215],"can":[55],"indicate":[56],"flaws":[57],"model's":[60],"knowledge":[61],"representation":[62],"or":[63],"operational":[64],"behavior.":[65],"However,":[66],"producing":[67],"high-quality":[68],"at":[70],"scale":[71],"remains":[72],"challenging,":[73],"primarily":[74],"because":[75],"it":[76],"requires":[77],"human":[78,92,140],"experts":[79,93],"ensure":[81],"reliability":[83],"probes.":[86,132],"Prior":[87],"work":[88],"has":[89],"relied":[90],"on":[91,187,203],"manually":[95],"verify":[96],"each":[97],"individual":[98],"probe,":[99],"making":[100],"process":[102],"expensive,":[103],"resource-intensive,":[104],"prone":[106],"subjectivity.":[108],"o":[109],"address":[110],"limitations,":[112],"we":[113],"introduce":[114],"LLMAuditor,":[115],"a":[116,120,159,165,188,219],"framework":[117],"that":[118],"uses":[119],"human-in-the-loop":[121],"(HIL)":[122],"validated":[123],"prompt":[124,167,221],"template":[125,222],"guide":[127],"generating":[131],"This":[133,179],"approach":[134,181],"eliminates":[135],"need":[137],"exhaustive":[139],"verification":[141],"every":[143],"probe":[144,224],"while":[145],"maintaining":[146],"high":[147],"standards":[148],"quality":[150],"reliability.":[152],"LLMAuditor":[153,207],"operates":[154],"two":[156],"phases:":[157],"first,":[158],"helper":[160],"generates":[162],"HIL-validated":[166,220],"template;":[168],"second,":[169],"used":[173],"audit":[175],"target":[177],"LLM.":[178],"dual-LLM":[180],"ensures":[182],"verifiability,":[183],"avoids":[184],"circular":[185],"reliance":[186],"single":[189],"model,":[190],"enhances":[192,227],"rigor":[194],"generalizability":[196],"process.":[200],"Case":[201],"studies":[202],"different":[204],"show":[206],"reliably":[208],"identifies":[209],"inconsistencies.":[210],"The":[211],"framework's":[212],"novelty":[213],"lies":[214],"its":[216],"use":[217],"generation,":[225],"which":[226],"both":[228],"transparency":[230],"effectiveness":[232],"evaluation.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":8}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-12-03T00:00:00"}