{"id":"https://openalex.org/W4385488983","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191141","title":"Pros and Cons of Weight Pruning for Out-of-Distribution Detection: An Empirical Survey","display_name":"Pros and Cons of Weight Pruning for Out-of-Distribution Detection: An Empirical Survey","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385488983","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191141"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191141","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","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/A5051573944","display_name":"Satoru Koda","orcid":"https://orcid.org/0000-0002-9187-9625"},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoru Koda","raw_affiliation_strings":["Fujitsu Limited,AI Trust Research Centre,Japan","AI Trust Research Centre, Fujitsu Limited, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Limited,AI Trust Research Centre,Japan","institution_ids":["https://openalex.org/I2252096349"]},{"raw_affiliation_string":"AI Trust Research Centre, Fujitsu Limited, Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033720635","display_name":"Alon Zolfi","orcid":"https://orcid.org/0000-0003-0270-1743"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Alon Zolfi","raw_affiliation_strings":["Ben-Gurion University of the Negev,Department of Software and Information Systems Engineering,Israel","Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev,Department of Software and Information Systems Engineering,Israel","institution_ids":["https://openalex.org/I124227911"]},{"raw_affiliation_string":"Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055199255","display_name":"Edita Grolman","orcid":"https://orcid.org/0000-0002-8502-2035"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Edita Grolman","raw_affiliation_strings":["Ben-Gurion University of the Negev,Department of Software and Information Systems Engineering,Israel","Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev,Department of Software and Information Systems Engineering,Israel","institution_ids":["https://openalex.org/I124227911"]},{"raw_affiliation_string":"Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002391103","display_name":"Asaf Shabtai","orcid":"https://orcid.org/0000-0003-0630-4059"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Asaf Shabtai","raw_affiliation_strings":["Ben-Gurion University of the Negev,Department of Software and Information Systems Engineering,Israel","Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev,Department of Software and Information Systems Engineering,Israel","institution_ids":["https://openalex.org/I124227911"]},{"raw_affiliation_string":"Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075800271","display_name":"Ikuya Morikawa","orcid":null},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ikuya Morikawa","raw_affiliation_strings":["Fujitsu Limited,AI Trust Research Centre,Japan","AI Trust Research Centre, Fujitsu Limited, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Limited,AI Trust Research Centre,Japan","institution_ids":["https://openalex.org/I2252096349"]},{"raw_affiliation_string":"AI Trust Research Centre, Fujitsu Limited, Japan","institution_ids":["https://openalex.org/I2252096349"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072913672","display_name":"Yuval Elovici","orcid":"https://orcid.org/0000-0002-9641-128X"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yuval Elovici","raw_affiliation_strings":["Ben-Gurion University of the Negev,Department of Software and Information Systems Engineering,Israel","Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev,Department of Software and Information Systems Engineering,Israel","institution_ids":["https://openalex.org/I124227911"]},{"raw_affiliation_string":"Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Israel","institution_ids":["https://openalex.org/I124227911"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"abs 1506 3365","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9991999864578247,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980999827384949,"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/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.8068078756332397},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7677336931228638},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6459705233573914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5377329587936401},{"id":"https://openalex.org/keywords/weight-distribution","display_name":"Weight distribution","score":0.4919454753398895},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4800078272819519},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4662690758705139},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46531394124031067},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06844669580459595}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.8068078756332397},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7677336931228638},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6459705233573914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5377329587936401},{"id":"https://openalex.org/C25432639","wikidata":"https://www.wikidata.org/wiki/Q3711790","display_name":"Weight distribution","level":2,"score":0.4919454753398895},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4800078272819519},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4662690758705139},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46531394124031067},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06844669580459595},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191141","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","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":72,"referenced_works":["https://openalex.org/W967544008","https://openalex.org/W1493526108","https://openalex.org/W2033918639","https://openalex.org/W2125389748","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2335728318","https://openalex.org/W2531327146","https://openalex.org/W2732026016","https://openalex.org/W2767414122","https://openalex.org/W2787720882","https://openalex.org/W2867167548","https://openalex.org/W2887894061","https://openalex.org/W2894740066","https://openalex.org/W2942810103","https://openalex.org/W2951883849","https://openalex.org/W2963384319","https://openalex.org/W2963703618","https://openalex.org/W2963995504","https://openalex.org/W2965862774","https://openalex.org/W2978017171","https://openalex.org/W2986193249","https://openalex.org/W2990064013","https://openalex.org/W3005692288","https://openalex.org/W3005842225","https://openalex.org/W3008896913","https://openalex.org/W3038012435","https://openalex.org/W3043138801","https://openalex.org/W3092527263","https://openalex.org/W3118608800","https://openalex.org/W3134332063","https://openalex.org/W3153208318","https://openalex.org/W3171163219","https://openalex.org/W3214903388","https://openalex.org/W3216820735","https://openalex.org/W4226283624","https://openalex.org/W4231109964","https://openalex.org/W4285070005","https://openalex.org/W4287724856","https://openalex.org/W4287828539","https://openalex.org/W4296596384","https://openalex.org/W4296604211","https://openalex.org/W4312284582","https://openalex.org/W6625168331","https://openalex.org/W6677103964","https://openalex.org/W6678583879","https://openalex.org/W6684191040","https://openalex.org/W6728622933","https://openalex.org/W6743446608","https://openalex.org/W6745553787","https://openalex.org/W6745891213","https://openalex.org/W6748682750","https://openalex.org/W6752760542","https://openalex.org/W6753772360","https://openalex.org/W6755166560","https://openalex.org/W6757615711","https://openalex.org/W6761472960","https://openalex.org/W6768851824","https://openalex.org/W6771369672","https://openalex.org/W6772027524","https://openalex.org/W6773934161","https://openalex.org/W6774302960","https://openalex.org/W6780616643","https://openalex.org/W6780874654","https://openalex.org/W6784323503","https://openalex.org/W6794006112","https://openalex.org/W6797078281","https://openalex.org/W6803950395","https://openalex.org/W6811415122","https://openalex.org/W6839645004","https://openalex.org/W6842891282","https://openalex.org/W6843065753"],"related_works":["https://openalex.org/W4382795578","https://openalex.org/W2355463328","https://openalex.org/W2402648945","https://openalex.org/W1431147547","https://openalex.org/W2771741613","https://openalex.org/W2055761197","https://openalex.org/W2053213469","https://openalex.org/W2057608111","https://openalex.org/W2793032185","https://openalex.org/W939486154"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs)":[3],"perform":[4],"well":[5],"on":[6,77,84,127,155],"samples":[7,29,47,156],"from":[8,30,34],"the":[9,16,28,35,43,58,103,132,152,160,186,195],"training":[10,36],"distribution.":[11,37],"However,":[12],"DNNs":[13,44,64,142,211],"deployed":[14],"in":[15,68],"real":[17],"world":[18],"are":[19,167,171],"exposed":[20],"to":[21,27,42,90,144,159,191,212],"out-of-distribution":[22],"(OOD)":[23],"samples,":[24],"which":[25,123,150],"refer":[26],"distributions":[31],"that":[32,166,208],"differ":[33],"OOD":[38,46,66,74,93,112,125,153,175,215],"detection":[39,67,75,94,113,121,126,138,154,216],"is":[40],"indispensable":[41],"as":[45,185],"can":[48],"cause":[49],"unexpected":[50],"behaviors":[51],"for":[52,65,169,174],"them.":[53],"This":[54],"paper":[55],"empirically":[56],"explores":[57],"effectiveness":[59],"of":[60,63,96,148,188,197,204],"weight":[61,179,206],"pruning":[62,110,207],"a":[69,118],"post-hoc":[70],"setting":[71],"(i.e.,":[72],"performing":[73],"based":[76],"pretrained":[78],"DNN":[79,128,205],"models).":[80],"We":[81],"conduct":[82],"experiments":[83],"image,":[85],"text,":[86],"and":[87,177,217],"tabular":[88],"datasets":[89],"thoroughly":[91],"evaluate":[92],"performance":[95],"weight-pruned":[97,210],"DNNs.":[98],"Our":[99],"experimental":[100],"results":[101],"bring":[102],"following":[104],"three":[105],"novel":[106],"findings:":[107],"(i)":[108],"Weight":[109],"improves":[111,151],"per-formance":[114],"more":[115],"significantly":[116],"with":[117,136],"Mahalanobis":[119,133],"distance-based":[120],"approach,":[122],"performs":[124],"hidden":[129],"representations":[130],"using":[131],"distance,":[134],"than":[135],"logit-based":[137],"approaches.":[139],"(ii)":[140],"Weight-pruned":[141],"tend":[143],"extract":[145],"global":[146],"features":[147],"inputs,":[149],"much":[157],"dissimilar":[158],"in-distribution":[161],"samples.":[162],"(iii)":[163],"The":[164],"weights":[165,189],"useless":[168],"classification":[170,192,218],"often":[172],"useful":[173],"detection,":[176],"thus":[178],"importance":[180],"should":[181],"not":[182],"be":[183],"quantified":[184],"sensitivity":[187],"only":[190],"error.":[193],"On":[194],"basis":[196],"these":[198],"findings,":[199],"we":[200],"advocate":[201],"practical":[202],"techniques":[203],"enable":[209],"maintain":[213],"both":[214],"capabilities.":[219]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}