{"id":"https://openalex.org/W4415708920","doi":"https://doi.org/10.1109/icme59968.2025.11210114","title":"MIINT: Infuse Intuitive Data Correspondence for Model Interpretation","display_name":"MIINT: Infuse Intuitive Data Correspondence for Model Interpretation","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415708920","doi":"https://doi.org/10.1109/icme59968.2025.11210114"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11210114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11210114","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065255268","display_name":"Yuyang Wang","orcid":"https://orcid.org/0000-0002-3822-0389"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyang Wang","raw_affiliation_strings":["Nanjing University,National Key Laboratory for Novel Software Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University,National Key Laboratory for Novel Software Technology","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036356449","display_name":"Ligeng Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ligeng Chen","raw_affiliation_strings":["Nanjing University,National Key Laboratory for Novel Software Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University,National Key Laboratory for Novel Software Technology","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032564674","display_name":"Bing Mao","orcid":null},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Mao","raw_affiliation_strings":["Nanjing University,National Key Laboratory for Novel Software Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University,National Key Laboratory for Novel Software Technology","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27879829,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.984499990940094,"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":0.984499990940094,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0026000000070780516,"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"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","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"}}],"keywords":[{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5490000247955322},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.5184999704360962},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.48399999737739563},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4796999990940094},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45809999108314514},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.4390999972820282},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41940000653266907},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.41749998927116394},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4162999987602234}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7408000230789185},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7024999856948853},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6050000190734863},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5490000247955322},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.5184999704360962},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.48399999737739563},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4796999990940094},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.4390999972820282},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41940000653266907},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4162999987602234},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4162999987602234},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4077000021934509},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.40540000796318054},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.38839998841285706},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.29660001397132874},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.29089999198913574},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2849999964237213},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2565999925136566}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11210114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11210114","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1678356000","https://openalex.org/W1955942245","https://openalex.org/W1965555277","https://openalex.org/W1977295328","https://openalex.org/W2094839437","https://openalex.org/W2194775991","https://openalex.org/W2516809705","https://openalex.org/W2946444107","https://openalex.org/W2959587146","https://openalex.org/W3005086430","https://openalex.org/W3167451058","https://openalex.org/W4280578116","https://openalex.org/W4402783647","https://openalex.org/W6950310954"],"related_works":[],"abstract_inverted_index":{"To":[0,48],"help":[1],"humans":[2],"understand":[3],"the":[4,17,50,65,69,96,99,102,119,139,153],"mechanism":[5],"of":[6,20,26,52,91],"machine":[7,54,123],"learning":[8,22,55,124],"models":[9],"seamlessly,":[10],"various":[11],"works":[12],"are":[13,61],"dedicated":[14],"to":[15,30,37,94,113],"opening":[16],"black":[18],"boxes":[19],"current":[21],"methods.":[23],"The":[24],"mainstream":[25],"existing":[27],"work":[28],"attempts":[29],"calculate":[31],"feature":[32],"importance":[33],"directly":[34],"from":[35,42],"input":[36],"output":[38],"but":[39],"still":[40],"suffers":[41],"infidelity,":[43],"inconsistency,":[44],"instability,":[45],"and":[46,68,101,138,149,160,166,169,175],"complexity.":[47],"improve":[49],"performance":[51],"interpretable":[53,122],"methods,":[56],"we":[57,110],"find":[58],"that":[59,142],"there":[60],"natural":[62],"correlations":[63],"between":[64,98],"prediction":[66],"results":[67,140],"features":[70],"under":[71],"specific":[72],"tasks,":[73,82],"called":[74],"intuitive":[75,92,115],"data":[76,116],"correspondence.":[77],"Specifically,":[78],"in":[79],"image":[80,83,135],"classification":[81,103,136],"segmentation":[84],"can":[85],"be":[86],"regarded":[87],"as":[88],"a":[89],"kind":[90],"selection":[93],"sketch":[95],"relationship":[97],"object":[100],"result.":[104],"Based":[105],"on":[106,132],"this":[107],"heuristic":[108],"observation,":[109],"propose":[111],"MIINT":[112,143,157],"integrate":[114],"correspondence":[117],"into":[118],"traditional":[120],"post-hoc":[121],"techniques":[125],"with":[126,152],"partial":[127],"dependency.":[128],"We":[129],"conduct":[130],"experiments":[131],"2":[133],"classic":[134],"datasets,":[137],"show":[141],"has":[144],"better":[145],"fidelity,":[146],"consistency,":[147],"stability,":[148],"sparsity":[150],"compared":[151],"baseline":[154],"method":[155],"LIME:":[156],"reduces":[158],"infidelity":[159],"complexity":[161],"by":[162,171],"more":[163,172],"than":[164,173],"10%,":[165],"increases":[167],"consistency":[168],"stability":[170],"10%":[174],"25%":[176],"respectively.":[177]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-30T00:00:00"}