{"id":"https://openalex.org/W7138014021","doi":"https://doi.org/10.1609/aaai.v40i38.40456","title":"Query-Efficient Domain Knowledge Stealing Against Large Language Models","display_name":"Query-Efficient Domain Knowledge Stealing Against Large Language Models","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138014021","doi":"https://doi.org/10.1609/aaai.v40i38.40456"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i38.40456","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i38.40456","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40456/44417","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40456/44417","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129654558","display_name":"Zhengao Li","orcid":null},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhengao Li","raw_affiliation_strings":["Florida State University"],"affiliations":[{"raw_affiliation_string":"Florida State University","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129685412","display_name":"Xiaopeng Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaopeng Yuan","raw_affiliation_strings":["University of California, Los Angeles"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042752180","display_name":"Bolin Shen","orcid":"https://orcid.org/0000-0002-6471-9183"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bolin Shen","raw_affiliation_strings":["Florida State University"],"affiliations":[{"raw_affiliation_string":"Florida State University","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129718997","display_name":"Kien Le","orcid":null},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kien Le","raw_affiliation_strings":["Florida State University"],"affiliations":[{"raw_affiliation_string":"Florida State University","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129742310","display_name":"Haohan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haohan Wang","raw_affiliation_strings":["University of Illinois at Urbana-Champaign"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084919916","display_name":"Xugui Zhou","orcid":"https://orcid.org/0000-0002-3663-7447"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xugui Zhou","raw_affiliation_strings":["Louisiana State University"],"affiliations":[{"raw_affiliation_string":"Louisiana State University","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020498118","display_name":"Shangqian Gao","orcid":"https://orcid.org/0000-0001-9699-1790"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shangqian Gao","raw_affiliation_strings":["Florida State University"],"affiliations":[{"raw_affiliation_string":"Florida State University","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129681181","display_name":"Yushun Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yushun Dong","raw_affiliation_strings":["Florida State University"],"affiliations":[{"raw_affiliation_string":"Florida State University","institution_ids":["https://openalex.org/I103163165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5129654558"],"corresponding_institution_ids":["https://openalex.org/I103163165"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23554604,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"38","first_page":"31870","last_page":"31878"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.5767999887466431,"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":0.5767999887466431,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.10189999639987946,"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":0.07970000058412552,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.7052000164985657},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.6086000204086304},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5759000182151794},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.44369998574256897},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.435699999332428},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.35679998993873596},{"id":"https://openalex.org/keywords/domain-model","display_name":"Domain model","score":0.3538999855518341},{"id":"https://openalex.org/keywords/domain-analysis","display_name":"Domain analysis","score":0.3418000042438507}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7882999777793884},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.7052000164985657},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.6086000204086304},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5759000182151794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44519999623298645},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.44369998574256897},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.435699999332428},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4221000075340271},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C92548554","wikidata":"https://www.wikidata.org/wiki/Q2262868","display_name":"Domain model","level":3,"score":0.3538999855518341},{"id":"https://openalex.org/C15708719","wikidata":"https://www.wikidata.org/wiki/Q2271801","display_name":"Domain analysis","level":5,"score":0.3418000042438507},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C84685590","wikidata":"https://www.wikidata.org/wiki/Q1540472","display_name":"Knowledge engineering","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C135257023","wikidata":"https://www.wikidata.org/wiki/Q691358","display_name":"Domain-specific language","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C31084985","wikidata":"https://www.wikidata.org/wiki/Q372650","display_name":"Common knowledge (logic)","level":5,"score":0.2671000063419342},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26269999146461487},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C2777220311","wikidata":"https://www.wikidata.org/wiki/Q6423340","display_name":"Knowledge acquisition","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i38.40456","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i38.40456","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40456/44417","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i38.40456","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i38.40456","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40456/44417","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138014021.pdf","grobid_xml":"https://content.openalex.org/works/W7138014021.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1,96],"models":[2],"(LLMs)":[3],"concentrate":[4],"substantial":[5],"knowledge":[6,44,92,121,178],"in":[7,60,186],"specialized":[8],"domains":[9],"due":[10],"to":[11,22,32,71,168],"extensive":[12],"pretraining":[13],"and":[14,17,24,69,76,118,128,136,148,157,164,191,193],"instruction":[15],"tuning,":[16],"they":[18],"are":[19],"now":[20],"central":[21],"commercial":[23],"scientific":[25],"practice.":[26],"Yet":[27],"access":[28],"is":[29,52],"usually":[30],"limited":[31],"costly,":[33],"rate-limited":[34],"interfaces,":[35],"which":[36],"motivates":[37],"methods":[38],"that":[39,53,78,111,144],"can":[40],"extract":[41],"targeted":[42],"domain":[43,56,120,134,177],"with":[45],"minimal":[46],"querying":[47],"effort.":[48],"A":[49,151],"further":[50],"challenge":[51],"the":[54,73,80,113,116,155,160,184],"target":[55],"may":[57],"be":[58],"unknown":[59],"advance,":[61],"so":[62],"naive":[63],"or":[64,103,179],"generic":[65,104],"prompts":[66],"waste":[67],"queries":[68],"fail":[70],"expose":[72],"underlying":[74],"concepts":[75],"relations":[77,139],"structure":[79],"domain.":[81],"In":[82],"this":[83,166],"work,":[84],"we":[85],"introduce":[86],"a":[87,126],"query-efficient":[88],"approach":[89],"for":[90],"domain-specific":[91],"stealing":[93],"from":[94,125],"black-box":[95],"models.":[97],"Rather":[98],"than":[99],"issuing":[100],"random":[101],"questions":[102],"templates,":[105],"our":[106],"framework":[107],"performs":[108],"self-directed":[109],"exploration":[110],"lets":[112],"model":[114,163],"find":[115],"direction":[117],"mine":[119],"by":[122],"itself.":[123],"Starting":[124],"small":[127],"diverse":[129],"seed,":[130],"it":[131],"discovers":[132],"salient":[133],"entities":[135],"induces":[137],"their":[138],"through":[140],"structured":[141],"question":[142],"families":[143],"elicit":[145],"definitional,":[146],"functional,":[147],"compositional":[149],"information.":[150],"feedback-driven":[152],"controller":[153],"analyzes":[154],"errors":[156],"uncertainty":[158],"of":[159],"extracted":[161],"surrogate":[162],"uses":[165],"signal":[167],"refine":[169],"subsequent":[170],"queries,":[171],"all":[172],"without":[173],"relying":[174],"on":[175],"prior":[176],"external":[180],"resources.":[181],"We":[182],"evaluate":[183],"method":[185],"two":[187],"expert-centric":[188],"settings,":[189],"medicine":[190],"finance,":[192],"observe":[194],"consistently":[195],"better":[196],"performance":[197],"while":[198],"requiring":[199],"significantly":[200],"fewer":[201],"queries.":[202]},"counts_by_year":[],"updated_date":"2026-03-20T20:47:17.329874","created_date":"2026-03-18T00:00:00"}