{"id":"https://openalex.org/W4400811374","doi":"https://doi.org/10.1109/aicas59952.2024.10595859","title":"Optimizing Vision Transformers: Leveraging Max and Min Operations for Efficient Pruning","display_name":"Optimizing Vision Transformers: Leveraging Max and Min Operations for Efficient Pruning","publication_year":2024,"publication_date":"2024-04-22","ids":{"openalex":"https://openalex.org/W4400811374","doi":"https://doi.org/10.1109/aicas59952.2024.10595859"},"language":"en","primary_location":{"id":"doi:10.1109/aicas59952.2024.10595859","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/aicas59952.2024.10595859","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS)","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/A5065084602","display_name":"Philippe Bich","orcid":"https://orcid.org/0000-0001-9011-7437"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Philippe Bich","raw_affiliation_strings":["Politecnico di Torino,DET,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DET,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013322141","display_name":"Chiara Boretti","orcid":"https://orcid.org/0000-0003-0278-4593"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Chiara Boretti","raw_affiliation_strings":["Politecnico di Torino,DET,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DET,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032387854","display_name":"Luciano Prono","orcid":"https://orcid.org/0000-0003-1507-9092"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luciano Prono","raw_affiliation_strings":["Politecnico di Torino,DET,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DET,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019602694","display_name":"Fabio Pareschi","orcid":"https://orcid.org/0000-0001-8777-7135"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabio Pareschi","raw_affiliation_strings":["Politecnico di Torino,DET,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DET,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088876922","display_name":"Riccardo Rovatti","orcid":"https://orcid.org/0000-0002-4731-7860"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Riccardo Rovatti","raw_affiliation_strings":["University of Bologna,DEI,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bologna,DEI,Italy","institution_ids":["https://openalex.org/I9360294"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062714455","display_name":"Gianluca Setti","orcid":"https://orcid.org/0000-0002-2496-1856"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Gianluca Setti","raw_affiliation_strings":["King Abdullah University of Science and Technology (KAUST),CEMSE,Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King Abdullah University of Science and Technology (KAUST),CEMSE,Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9619,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.76528302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"28","issue":null,"first_page":"337","last_page":"341"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.8883000016212463,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.8883000016212463,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6222885251045227},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5996172428131104},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5558644533157349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5064622163772583},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37609219551086426},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33726173639297485},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17857971787452698},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.12254995107650757},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.06703916192054749}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6222885251045227},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5996172428131104},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5558644533157349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5064622163772583},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37609219551086426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33726173639297485},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17857971787452698},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.12254995107650757},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.06703916192054749},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/aicas59952.2024.10595859","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/aicas59952.2024.10595859","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS)","raw_type":"proceedings-article"},{"id":"pmh:oai:cris.unibo.it:11585/1049039","is_oa":false,"landing_page_url":"https://hdl.handle.net/11585/1049039","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W2112796928","https://openalex.org/W2194775991","https://openalex.org/W2747329762","https://openalex.org/W2750384547","https://openalex.org/W2905810301","https://openalex.org/W2963363373","https://openalex.org/W3014641619","https://openalex.org/W3019166713","https://openalex.org/W3045735558","https://openalex.org/W3091825101","https://openalex.org/W3094502228","https://openalex.org/W3159788821","https://openalex.org/W3175149871","https://openalex.org/W4212774754","https://openalex.org/W4225595226","https://openalex.org/W4246193833","https://openalex.org/W4309242452","https://openalex.org/W4312264301","https://openalex.org/W4313641686","https://openalex.org/W4383108355","https://openalex.org/W6743688258","https://openalex.org/W6770765273","https://openalex.org/W6772027524","https://openalex.org/W6774302960","https://openalex.org/W6784333009","https://openalex.org/W6787972765","https://openalex.org/W6797213061","https://openalex.org/W6797972850","https://openalex.org/W6852956349"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W2058170566","https://openalex.org/W4306674287","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407"],"abstract_inverted_index":{"The":[0],"research":[1],"on":[2,37,92,189],"Deep":[3],"Neural":[4],"Networks":[5],"(DNNs)":[6],"continues":[7],"to":[8,29,71,99,115,163,201],"enhance":[9],"the":[10,30,46,73,78,87,93,100,111,116,124,147,155,176,180,202],"performance":[11],"of":[12,19,32,48,59,75,89,118,158,184],"these":[13],"models":[14],"over":[15],"a":[16,68,105,134,185],"wide":[17],"spectrum":[18],"tasks,":[20],"increasing":[21],"their":[22,34,60],"adoption":[23],"in":[24,77,104,133,146],"many":[25,127],"fields.":[26],"This":[27,84,109],"leads":[28],"need":[31],"extending":[33],"usage":[35,88,117],"also":[36],"edge":[38],"devices":[39],"with":[40,45,141],"limited":[41],"resources,":[42],"even":[43],"though,":[44],"advent":[47],"Transformer-based":[49],"models,":[50],"this":[51,63],"has":[52],"become":[53],"an":[54,97],"increasingly":[55],"complex":[56],"task":[57],"because":[58],"size.":[61],"In":[62,168],"context,":[64],"pruning":[65,143],"emerges":[66],"as":[67],"crucial":[69],"tool":[70],"reduce":[72],"number":[74],"weights":[76,194],"memory-hungry":[79],"Fully":[80],"Connected":[81],"(FC)":[82],"layers.":[83],"paper":[85],"explores":[86],"neurons":[90,197],"based":[91],"Multiply-And-Max/min":[94],"(MAM)":[95],"operation,":[96],"alternative":[98],"conventional":[101],"Multiply-and-Accumulate":[102],"(MAC),":[103],"Vision":[106],"Transformer":[107],"(ViT).":[108],"enhances":[110],"model":[112,138],"prunability":[113],"thanks":[114],"Max":[119],"and":[120,139],"Min":[121],"operations.":[122],"For":[123],"first":[125],"time,":[126],"MAM-based":[128,152],"FC":[129,177],"layers":[130,153,160,178],"are":[131,198],"used":[132],"large":[135],"state-of-the-art":[136],"DNN":[137],"compressed":[140],"various":[142],"techniques":[144],"available":[145],"literature.":[148],"Experiments":[149],"show":[150],"that":[151,205],"achieve":[154],"same":[156],"accuracy":[157],"traditional":[159,209],"using":[161,171,208],"up":[162],"12":[164],"times":[165],"less":[166],"weights.":[167],"particular,":[169],"when":[170,207],"Global":[172],"Magnitude":[173],"Pruning":[174],"(GMP),":[175],"following":[179],"Multi-head":[181],"Attention":[182],"block":[183],"ViT-B/16":[186],"model,":[187],"fine-tuned":[188],"CIFAR-100,":[190],"count":[191],"only":[192],"560000":[193],"if":[195],"MAM":[196],"used,":[199],"compared":[200],"31.4":[203],"million":[204],"remain":[206],"MAC":[210],"neurons.":[211]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}