{"id":"https://openalex.org/W7153324030","doi":"https://doi.org/10.1002/aaai.70058","title":"Teach AI What It Doesn't Know","display_name":"Teach AI What It Doesn't Know","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7153324030","doi":"https://doi.org/10.1002/aaai.70058"},"language":"en","primary_location":{"id":"doi:10.1002/aaai.70058","is_oa":true,"landing_page_url":"https://doi.org/10.1002/aaai.70058","pdf_url":null,"source":{"id":"https://openalex.org/S163019073","display_name":"AI Magazine","issn_l":"0738-4602","issn":["0738-4602","2371-9621"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AI Magazine","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1002/aaai.70058","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133351526","display_name":"Sean Du","orcid":"https://orcid.org/0000-0002-8080-7861"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Sean Du","raw_affiliation_strings":["College of Computing and Data Science Nanyang Technological University Singapore Singapore"],"raw_orcid":"https://orcid.org/0000-0002-8080-7861","affiliations":[{"raw_affiliation_string":"College of Computing and Data Science Nanyang Technological University Singapore Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5133351526"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.62329803,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"47","issue":"2","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":0.421099990606308,"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":0.421099990606308,"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":0.27239999175071716,"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":0.05490000173449516,"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/reliability","display_name":"Reliability (semiconductor)","score":0.6068000197410583},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.49709999561309814},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.49570000171661377},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4814999997615814},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.43810001015663147},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.41620001196861267},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3490000069141388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.708899974822998},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6068000197410583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5778999924659729},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.49709999561309814},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.49570000171661377},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4814999997615814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4458000063896179},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.43810001015663147},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.41620001196861267},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/aaai.70058","is_oa":true,"landing_page_url":"https://doi.org/10.1002/aaai.70058","pdf_url":null,"source":{"id":"https://openalex.org/S163019073","display_name":"AI Magazine","issn_l":"0738-4602","issn":["0738-4602","2371-9621"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AI Magazine","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1002/aaai.70058","is_oa":true,"landing_page_url":"https://doi.org/10.1002/aaai.70058","pdf_url":null,"source":{"id":"https://openalex.org/S163019073","display_name":"AI Magazine","issn_l":"0738-4602","issn":["0738-4602","2371-9621"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AI Magazine","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7495356202125549,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1932198206","https://openalex.org/W2940927497","https://openalex.org/W2964424332","https://openalex.org/W2970373549","https://openalex.org/W2970489881","https://openalex.org/W2971218990","https://openalex.org/W3035564946","https://openalex.org/W3088877992","https://openalex.org/W4312640451","https://openalex.org/W4385572696","https://openalex.org/W4389520157","https://openalex.org/W4390190605","https://openalex.org/W4391140530","https://openalex.org/W4394593203","https://openalex.org/W4394625526","https://openalex.org/W4403780697","https://openalex.org/W4404544600","https://openalex.org/W4404769985","https://openalex.org/W4409365591","https://openalex.org/W4415796039","https://openalex.org/W7133205527","https://openalex.org/W7133221474"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"AI":[1,174],"systems":[2,175],"are":[3],"rapidly":[4],"transitioning":[5],"from":[6],"laboratory":[7],"demonstrations":[8],"to":[9,22,146],"decision\u2010making":[10],"technologies":[11],"deployed":[12],"in":[13,153,182],"high\u2010stakes":[14],"domains.":[15],"Yet":[16],"reliability":[17,74,138],"remains":[18],"a":[19,75,169],"primary":[20],"obstacle":[21],"responsible":[23],"adoption:":[24],"discriminative":[25],"models":[26,37,43],"can":[27,45],"be":[28],"confidently":[29],"wrong":[30],"under":[31,116,132],"out\u2010of\u2010distribution":[32],"(OOD)":[33],"inputs,":[34],"and":[35,70,90,98,118,124,130,156,180],"foundation":[36],"(FMs)":[38],"such":[39],"as":[40],"large":[41],"language":[42],"(LLMs)":[44],"generate":[46],"fluent":[47],"but":[48],"untruthful,":[49],"harmful,":[50],"or":[51],"misaligned":[52],"outputs.":[53],"My":[54],"research":[55],"develops":[56],"the":[57,109],"foundations":[58],"of":[59],"reliable":[60],"machine":[61],"learning":[62,83,107],"with":[63,121],"minimal":[64],"human":[65],"supervision":[66],",":[67],"unifying":[68],"algorithms,":[69],"theory":[71],"that":[72,94,176],"make":[73],"first\u2010class":[76],"objective":[77],"alongside":[78],"accuracy.":[79],"I":[80,101,136],"advance":[81],"unknown\u2010aware":[82],"through":[84],"automated":[85],"outlier":[86],"generation,":[87],"introducing":[88],"feature\u2010":[89],"input\u2010space":[91],"synthesis":[92],"frameworks":[93,139],"regularize":[95],"decision":[96],"boundaries":[97],"improve":[99],"interpretability.":[100],"further":[102],"establish":[103],"principled":[104],"methods":[105],"for":[106,127,140,161,172],"\u201cin":[108],"wild\u201d":[110],"by":[111,142],"leveraging":[112],"unlabeled":[113,144],"deployment":[114],"data":[115,160],"mixture":[117],"contamination":[119],"models,":[120,155],"theoretical":[122],"guarantees":[123],"state\u2010of\u2010the\u2010art":[125],"performance":[126],"OOD":[128],"detection":[129],"generalization":[131],"diverse":[133],"shifts.":[134],"Finally,":[135],"design":[137],"FMs":[141],"exploiting":[143],"signals":[145],"detect":[147],"hallucinations,":[148],"defend":[149],"against":[150],"malicious":[151],"prompts":[152],"vision\u2013language":[154],"denoise":[157],"noisy":[158],"preference":[159],"more":[162],"dependable":[163],"alignment.":[164],"Collectively,":[165],"these":[166],"contributions":[167],"provide":[168],"cohesive":[170],"toolkit":[171],"deploying":[173],"remain":[177],"accurate,":[178],"calibrated,":[179],"trustworthy":[181],"open\u2010world":[183],"environments.":[184]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-04-11T00:00:00"}