{"id":"https://openalex.org/W7125959937","doi":"https://doi.org/10.1109/smc58881.2025.11343134","title":"MIP-Explainer: An Explainability Method for Graph Neural Networks Based on Mutual Information","display_name":"MIP-Explainer: An Explainability Method for Graph Neural Networks Based on Mutual Information","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125959937","doi":"https://doi.org/10.1109/smc58881.2025.11343134"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343134","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 Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"article","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/A5033856350","display_name":"Huijiang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huijiang Wang","raw_affiliation_strings":["Guangxi Normal University,Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education,Guilin,China,541004"],"affiliations":[{"raw_affiliation_string":"Guangxi Normal University,Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education,Guilin,China,541004","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019212486","display_name":"Q. X. Li","orcid":"https://orcid.org/0009-0006-9658-8727"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiyu Li","raw_affiliation_strings":["Guangxi Normal University,School of Computer Science and Engineering,Guilin,China,541004"],"affiliations":[{"raw_affiliation_string":"Guangxi Normal University,School of Computer Science and Engineering,Guilin,China,541004","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111799698","display_name":"Jing Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Tan","raw_affiliation_strings":["Guangxi Normal University,School of Computer Science and Engineering,Guilin,China,541004"],"affiliations":[{"raw_affiliation_string":"Guangxi Normal University,School of Computer Science and Engineering,Guilin,China,541004","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015957059","display_name":"Linlin Su","orcid":"https://orcid.org/0000-0002-7727-9607"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linlin Su","raw_affiliation_strings":["Guangxi Normal University,School of Computer Science and Engineering,Guilin,China,541004"],"affiliations":[{"raw_affiliation_string":"Guangxi Normal University,School of Computer Science and Engineering,Guilin,China,541004","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124078576","display_name":"Jinyan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyan Wang","raw_affiliation_strings":["Guangxi Normal University,Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education,Guilin,China,541004"],"affiliations":[{"raw_affiliation_string":"Guangxi Normal University,Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education,Guilin,China,541004","institution_ids":["https://openalex.org/I29739308"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5033856350"],"corresponding_institution_ids":["https://openalex.org/I29739308"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.8395781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2634","last_page":"2639"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.7044000029563904,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.7044000029563904,"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":0.2549999952316284,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.008200000040233135,"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/interpretability","display_name":"Interpretability","score":0.9575999975204468},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4943999946117401},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4781000018119812},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4731999933719635},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4569999873638153},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.34860000014305115},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.3379000127315521}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9575999975204468},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5730999708175659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5388000011444092},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4943999946117401},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4781000018119812},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4731999933719635},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4569999873638153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37779998779296875},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3504999876022339},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.34860000014305115},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3409999907016754},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.3379000127315521},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31540000438690186},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.25609999895095825},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343134","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 Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5601605176925659,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325559","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1977340881","https://openalex.org/W2008857988","https://openalex.org/W2277195237","https://openalex.org/W2808856341","https://openalex.org/W2955205099","https://openalex.org/W2962810718","https://openalex.org/W2983721890","https://openalex.org/W2997997679","https://openalex.org/W3000120900","https://openalex.org/W3032123378","https://openalex.org/W3035625410","https://openalex.org/W3116637551","https://openalex.org/W4252973173"],"related_works":[],"abstract_inverted_index":{"Graph":[0],"Neural":[1],"Networks":[2],"(GNNs)":[3],"garnered":[4],"significant":[5],"success":[6],"in":[7,15,25,31,47,111,121],"modeling":[8],"graphs":[9],"due":[10],"to":[11,39,98,149,173],"their":[12,29,40],"powerful":[13],"capabilities":[14],"representation":[16],"learning":[17],"and":[18,34,42,108,138,169,188],"reasoning.":[19],"However,":[20],"the":[21,75,81,84,99,115,142,151,159,162,192],"lack":[22],"of":[23,86,104,118,136,158,194],"explainability":[24,48],"GNNs":[26],"largely":[27],"limits":[28],"application":[30,103],"security,":[32],"sensitive,":[33],"other":[35],"such":[36],"scenarios.":[37],"Due":[38],"interpretability":[41,117],"high":[43],"fidelity,":[44],"surrogate":[45,63,119],"methods":[46],"techniques":[49],"have":[50],"sparked":[51],"some":[52],"explorations,":[53],"but":[54],"many":[55],"challenges":[56],"are":[57,96],"still":[58],"not":[59],"well-addressed.":[60],"1)":[61],"Most":[62],"based":[64],"explainers":[65],"generate":[66],"local":[67,156,175],"neighborhoods":[68,157],"by":[69,197],"randomly":[70],"perturbing":[71],"node":[72],"features,":[73],"ignoring":[74],"graph":[76,82,152],"topology":[77],"perturbations.":[78],"2)":[79],"As":[80],"grows,":[83],"combinations":[85,95],"perturbations":[87],"increase":[88],"exponentially,":[89],"whereas":[90],"only":[91],"a":[92,129],"few":[93],"perturbation":[94],"close":[97],"prediction.":[100],"3)":[101],"The":[102],"multiple":[105],"relaxation":[106,180],"steps":[107],"regularization":[109,182],"terms":[110],"practice":[112],"may":[113],"diminish":[114],"intrinsic":[116],"models":[120],"previous":[122],"works.":[123],"Towards":[124],"this":[125],"end,":[126],"we":[127,145,165],"propose":[128,166],"novel":[130],"framework":[131],"named":[132],"MIP-Explainer,":[133],"which":[134],"consists":[135],"Selector":[137,143],"Explainer":[139,163],"modules.":[140],"In":[141,161],"module,":[144,164],"leverage":[146],"mutual":[147],"information":[148],"perturb":[150],"structure,":[153],"efficiently":[154],"generating":[155],"data.":[160],"an":[167],"intuitive":[168],"interpretable":[170],"linear":[171],"model":[172],"these":[174],"neighborhoods,":[176],"without":[177],"incorporating":[178],"any":[179],"or":[181],"terms.":[183],"Extensive":[184],"experiments":[185],"on":[186],"real-world":[187],"synthetic":[189],"datasets":[190],"show":[191],"effectiveness":[193],"our":[195],"MIP-Explainer":[196],"outperforming":[198],"state-of-the-art":[199],"baselines.":[200]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-29T00:00:00"}