{"id":"https://openalex.org/W4362653432","doi":"https://doi.org/10.1109/access.2023.3264855","title":"Pay Attention via Quantization: Enhancing Explainability of Neural Networks via Quantized Activation","display_name":"Pay Attention via Quantization: Enhancing Explainability of Neural Networks via Quantized Activation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4362653432","doi":"https://doi.org/10.1109/access.2023.3264855"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3264855","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3264855","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10092762.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10092762.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025991089","display_name":"Yuma Tashiro","orcid":null},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuma Tashiro","raw_affiliation_strings":["Department of Information Systems Engineering, Graduate School of Information Science and Technology, Osaka University, Suita, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems Engineering, Graduate School of Information Science and Technology, Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102716651","display_name":"Hiromitsu Awano","orcid":"https://orcid.org/0000-0002-3674-4584"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiromitsu Awano","raw_affiliation_strings":["Department of Communications and Computer Engineering, Graduate School of Informatics, Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-3674-4584","affiliations":[{"raw_affiliation_string":"Department of Communications and Computer Engineering, Graduate School of Informatics, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6526,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.73675622,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"11","issue":null,"first_page":"34431","last_page":"34439"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9998000264167786,"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":0.9998000264167786,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9926999807357788,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9793000221252441,"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/computer-science","display_name":"Computer science","score":0.7934445142745972},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.671062707901001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6574793457984924},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.652924656867981},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6378564238548279},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6028815507888794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5225205421447754},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4619690775871277},{"id":"https://openalex.org/keywords/traffic-sign-recognition","display_name":"Traffic sign recognition","score":0.43771225214004517},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.4357629418373108},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33310121297836304},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.12835177779197693},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09309923648834229}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7934445142745972},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.671062707901001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6574793457984924},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.652924656867981},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6378564238548279},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6028815507888794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5225205421447754},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4619690775871277},{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.43771225214004517},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.4357629418373108},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33310121297836304},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.12835177779197693},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09309923648834229},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2023.3264855","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3264855","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10092762.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:irdb.nii.ac.jp:01221:0005929291","is_oa":true,"landing_page_url":"http://hdl.handle.net/2433/285273","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal article"},{"id":"pmh:oai:doaj.org/article:b997d13ac9e049e3a95d15f86ae8fe19","is_oa":true,"landing_page_url":"https://doaj.org/article/b997d13ac9e049e3a95d15f86ae8fe19","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 34431-34439 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3264855","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3264855","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10092762.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G870072910","display_name":null,"funder_award_id":"21H03409","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4362653432.pdf","grobid_xml":"https://content.openalex.org/works/W4362653432.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2342840547","https://openalex.org/W2516809705","https://openalex.org/W2891503716","https://openalex.org/W2958089299","https://openalex.org/W2962858109","https://openalex.org/W2963016445","https://openalex.org/W3015239370","https://openalex.org/W3034514369","https://openalex.org/W4294557331","https://openalex.org/W4296306278","https://openalex.org/W4312530540","https://openalex.org/W4385245566","https://openalex.org/W6637373629","https://openalex.org/W6684338915","https://openalex.org/W6684983439","https://openalex.org/W6693397755","https://openalex.org/W6704559304","https://openalex.org/W6752170072"],"related_works":["https://openalex.org/W4382897155","https://openalex.org/W4283820116","https://openalex.org/W3048636285","https://openalex.org/W2977842967","https://openalex.org/W2110143569","https://openalex.org/W4389041344","https://openalex.org/W3122938442","https://openalex.org/W2055243143","https://openalex.org/W4388684820","https://openalex.org/W2557202782"],"abstract_inverted_index":{"Modern":[0],"deep":[1,26,56],"learning":[2,27,57],"algorithms":[3],"comprise":[4],"highly":[5],"complex":[6],"artificial":[7],"neural":[8],"networks,":[9],"making":[10,42],"it":[11,43],"extremely":[12],"difficult":[13],"for":[14,52],"humans":[15],"to":[16,45,48,64,70,140,143,154,158],"track":[17],"their":[18],"inference":[19,36],"processes.":[20],"As":[21],"the":[22,29,50,53,66,93,96,102,111,121,144,155,160,167,172,186],"social":[23],"implementation":[24],"of":[25,55,98,105,185],"progresses,":[28],"human":[30],"and":[31,113],"economic":[32],"losses":[33],"caused":[34],"by":[35],"errors":[37],"are":[38,116],"becoming":[39],"increasingly":[40],"problematic,":[41],"necessary":[44],"develop":[46],"methods":[47],"explain":[49],"basis":[51],"decisions":[54],"algorithms.":[58],"Although":[59],"an":[60,75,150],"attention":[61,151],"mechanism-based":[62],"method":[63,174],"visualize":[65],"regions":[67],"that":[68,95,171],"contribute":[69],"steering":[71],"angle":[72],"prediction":[73],"in":[74,101,128,183],"automated":[76],"driving":[77],"task":[78],"has":[79,125],"been":[80,126],"proposed,":[81],"its":[82],"explanatory":[83,161],"capability":[84],"is":[85,108],"low.":[86],"In":[87],"this":[88,132],"paper,":[89],"we":[90,148],"focus":[91],"on":[92],"fact":[94],"importance":[97],"each":[99],"bit":[100,157],"activation":[103],"value":[104],"a":[106,176],"network":[107,135],"biased":[109],"(i.e.,":[110],"sign":[112,145,156],"exponent":[114],"bits":[115],"weighted":[117],"more":[118],"heavily":[119],"than":[120],"mantissa":[122],"bits),":[123],"which":[124],"overlooked":[127],"previous":[129],"studies.":[130],"Specifically,":[131],"paper":[133],"quantizes":[134],"activations,":[136],"encouraging":[137],"important":[138],"information":[139],"be":[141],"aggregated":[142],"bit.":[146],"Further,":[147],"introduce":[149],"mechanism":[152],"restricted":[153],"improve":[159],"power.":[162],"Our":[163],"numerical":[164],"experiment":[165],"using":[166],"Udacity":[168],"dataset":[169],"revealed":[170],"proposed":[173],"achieves":[175],"1.14\u00d7":[177],"higher":[178],"area":[179],"under":[180],"curve":[181],"(AUC)":[182],"terms":[184],"deletion":[187],"metric.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
