{"id":"https://openalex.org/W7138436613","doi":"https://doi.org/10.1609/aaai.v40i24.39065","title":"Rethinking Explanation Evaluation Under the Retraining Scheme","display_name":"Rethinking Explanation Evaluation Under the Retraining Scheme","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138436613","doi":"https://doi.org/10.1609/aaai.v40i24.39065"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i24.39065","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i24.39065","pdf_url":null,"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://doi.org/10.1609/aaai.v40i24.39065","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129720220","display_name":"Yi Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yi Cai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094191817","display_name":"Thibaud Ardoin","orcid":"https://orcid.org/0009-0001-4314-6769"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thibaud Ardoin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065997974","display_name":"Mayank Gulati","orcid":"https://orcid.org/0009-0002-7861-2018"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mayank Gulati","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5044286247","display_name":"Gerhard Wunder","orcid":"https://orcid.org/0009-0001-0850-8816"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gerhard Wunder","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5129720220"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64794007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"24","first_page":"19826","last_page":"19834"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.988099992275238,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.988099992275238,"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":0.0017000000225380063,"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":0.0017000000225380063,"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/retraining","display_name":"Retraining","score":0.758400022983551},{"id":"https://openalex.org/keywords/cognitive-reframing","display_name":"Cognitive reframing","score":0.5738000273704529},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5713000297546387},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5260000228881836},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5009999871253967},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.47049999237060547},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4674000144004822},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4138999879360199}],"concepts":[{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.758400022983551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6826000213623047},{"id":"https://openalex.org/C187029079","wikidata":"https://www.wikidata.org/wiki/Q958679","display_name":"Cognitive reframing","level":2,"score":0.5738000273704529},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5713000297546387},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5260000228881836},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5009999871253967},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.47049999237060547},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.4546000063419342},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4101000130176544},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40700000524520874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38350000977516174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37209999561309814},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.35440000891685486},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C2781270358","wikidata":"https://www.wikidata.org/wiki/Q5885594","display_name":"Holy Grail","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.289000004529953},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.28630000352859497},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.2605000138282776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i24.39065","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i24.39065","pdf_url":null,"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.v40i24.39065","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i24.39065","pdf_url":null,"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":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Feature":[0],"attribution":[1],"has":[2,31],"gained":[3],"prominence":[4],"as":[5,33,124],"a":[6,56,125,144,170],"tool":[7],"for":[8,129,191],"explaining":[9],"model":[10,48,87],"decisions,":[11],"yet":[12],"evaluating":[13],"explanation":[14,39,174],"quality":[15],"remains":[16],"challenging":[17],"due":[18],"to":[19,88],"the":[20,42,53,63,72,86,89,99,121,139,148,154,159,183,210],"absence":[21],"of":[22,44,74,102,147,212],"ground-truth":[23],"explanations.":[24],"To":[25],"circumvent":[26],"this,":[27],"explanation-guided":[28],"input":[29,45],"manipulation":[30],"emerged":[32],"an":[34],"indirect":[35],"evaluation":[36,95,149,180],"strategy,":[37],"measuring":[38],"effectiveness":[40],"through":[41],"impact":[43],"modifications":[46],"on":[47,138,158,173],"outcomes":[49],"during":[50],"inference.":[51],"Despite":[52],"widespread":[54],"use,":[55],"major":[57],"concern":[58],"with":[59],"inference-based":[60],"schemes":[61],"is":[62],"distribution":[64],"shift":[65],"caused":[66],"by":[67,84],"such":[68],"manipulations,":[69],"which":[70],"undermines":[71],"reliability":[73],"their":[75],"assessments.":[76],"The":[77],"retraining-based":[78,135],"scheme":[79],"ROAR":[80],"overcomes":[81],"this":[82,109],"issue":[83,123],"adapting":[85],"altered":[90],"data":[91,204],"distribution.":[92],"However,":[93],"its":[94],"results":[96,201],"often":[97],"contradict":[98],"theoretical":[100,115],"foundations":[101],"widely":[103],"accepted":[104],"explainers.":[105],"This":[106],"work":[107],"investigates":[108],"misalignment":[110],"between":[111],"empirical":[112,200],"observations":[113],"and":[114,194,219],"expectations.":[116],"In":[117],"particular,":[118],"we":[119,141,162],"identify":[120],"Sign":[122],"key":[126],"factor":[127],"responsible":[128],"residual":[130],"information":[131],"that":[132,143,167],"ultimately":[133],"distorts":[134],"evaluation.":[136,175],"Based":[137],"analysis,":[140],"show":[142],"straightforward":[145],"reframing":[146],"process":[150],"can":[151],"effectively":[152],"resolve":[153],"identified":[155],"issue.":[156],"Building":[157],"existing":[160],"framework,":[161],"further":[163],"propose":[164],"novel":[165],"variants":[166,177],"jointly":[168],"structure":[169],"comprehensive":[171],"perspective":[172],"These":[176],"largely":[178],"improve":[179],"efficiency":[181],"over":[182],"standard":[184],"retraining":[185],"protocol,":[186],"thereby":[187],"enhancing":[188],"practical":[189],"applicability":[190],"explainer":[192],"selection":[193],"benchmarking.":[195],"Following":[196],"our":[197],"proposed":[198],"schemes,":[199],"across":[202],"various":[203],"scales":[205],"provide":[206],"deeper":[207],"insights":[208],"into":[209],"performance":[211],"carefully":[213],"selected":[214],"explainers,":[215],"revealing":[216],"open":[217],"challenges":[218],"future":[220],"directions":[221],"in":[222],"explainability":[223],"research.":[224]},"counts_by_year":[],"updated_date":"2026-03-18T06:31:55.123368","created_date":"2026-03-18T00:00:00"}