{"id":"https://openalex.org/W4413925895","doi":"https://doi.org/10.1109/tpami.2025.3605239","title":"PRANCE: Joint Token-Optimization and Structural Channel-Pruning for Adaptive ViT Inference","display_name":"PRANCE: Joint Token-Optimization and Structural Channel-Pruning for Adaptive ViT Inference","publication_year":2025,"publication_date":"2025-09-02","ids":{"openalex":"https://openalex.org/W4413925895","doi":"https://doi.org/10.1109/tpami.2025.3605239","pmid":"https://pubmed.ncbi.nlm.nih.gov/40892654"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3605239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3605239","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ye Li","orcid":"https://orcid.org/0009-0008-9690-2119"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ye Li","raw_affiliation_strings":["Tsinghua University, Beijing, China","Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chen Tang","orcid":"https://orcid.org/0000-0002-0108-6729"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Tang","raw_affiliation_strings":["Tsinghua University, Beijing, China","Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuan Meng","orcid":"https://orcid.org/0000-0002-7450-9438"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Meng","raw_affiliation_strings":["Tsinghua University, Beijing, China","Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiajun Fan","orcid":"https://orcid.org/0000-0002-0263-2103"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jiajun Fan","raw_affiliation_strings":["Siebel School of Computing and Data Science, Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA","Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Siebel School of Computing and Data Science, Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003827815","display_name":"Zenghao Chai","orcid":"https://orcid.org/0000-0003-3709-4947"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zenghao Chai","raw_affiliation_strings":["Tsinghua University, Beijing, China","Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030101527","display_name":"Xinzhu Ma","orcid":"https://orcid.org/0000-0003-0504-0186"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xinzhu Ma","raw_affiliation_strings":["MMLab, Chinese University of Hong Kong, Shatin, Hong Kong","MMLab, The Chinese University of Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"MMLab, Chinese University of Hong Kong, Shatin, Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"MMLab, The Chinese University of Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhi Wang","orcid":"https://orcid.org/0000-0002-5462-6178"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China","Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100339293","display_name":"Wenwu Zhu","orcid":"https://orcid.org/0000-0003-2236-9290"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenwu Zhu","raw_affiliation_strings":["Tsinghua University, Beijing, China","Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21754806,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"48","issue":"1","first_page":"283","last_page":"298"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9918000102043152,"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"}},"topics":[{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9918000102043152,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9610999822616577,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9487000107765198,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.700171172618866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6512563228607178},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6503991484642029},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.6080312132835388},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5510421991348267},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4982185363769531},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4758472144603729},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39852920174598694},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37407276034355164},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11767706274986267},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09708848595619202}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.700171172618866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6512563228607178},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6503991484642029},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.6080312132835388},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5510421991348267},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4982185363769531},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4758472144603729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39852920174598694},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37407276034355164},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11767706274986267},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09708848595619202},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural 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":2,"locations":[{"id":"doi:10.1109/tpami.2025.3605239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3605239","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:40892654","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40892654","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G232973491","display_name":null,"funder_award_id":"62402264","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4264659296","display_name":null,"funder_award_id":"92467204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8973540564","display_name":null,"funder_award_id":"62472249","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2951360122","https://openalex.org/W3094502228","https://openalex.org/W3109946440","https://openalex.org/W3168622113","https://openalex.org/W3188427387","https://openalex.org/W3204801262","https://openalex.org/W4213019189","https://openalex.org/W4283811336","https://openalex.org/W4285601701","https://openalex.org/W4304142274","https://openalex.org/W4306870442","https://openalex.org/W4307092789","https://openalex.org/W4307504011","https://openalex.org/W4312310654","https://openalex.org/W4312772337","https://openalex.org/W4312849330","https://openalex.org/W4312910119","https://openalex.org/W4313142416","https://openalex.org/W4319300012","https://openalex.org/W4362500802","https://openalex.org/W4384820618","https://openalex.org/W4385198862","https://openalex.org/W4385245566","https://openalex.org/W4385391093","https://openalex.org/W4385768233","https://openalex.org/W4385801014","https://openalex.org/W4386075690","https://openalex.org/W4386076539","https://openalex.org/W4386076562","https://openalex.org/W4390691462","https://openalex.org/W4390873017","https://openalex.org/W4390873499","https://openalex.org/W4391147277","https://openalex.org/W4393160524","https://openalex.org/W4394625520","https://openalex.org/W4402716428","https://openalex.org/W4402753529"],"related_works":["https://openalex.org/W4388335561","https://openalex.org/W2970530566","https://openalex.org/W4288261899","https://openalex.org/W4307309205","https://openalex.org/W2967478618","https://openalex.org/W4385009901","https://openalex.org/W4385572700","https://openalex.org/W2997152889","https://openalex.org/W4285141722","https://openalex.org/W4387768015"],"abstract_inverted_index":{"The":[0],"troublesome":[1],"model":[2,27,175,183],"size":[3],"and":[4,29,56,62,99,115,127,166,185,247,268],"quadratic":[5],"computational":[6],"complexity":[7],"associated":[8],"with":[9,193],"token":[10,30,57,261],"quantity":[11],"pose":[12],"significant":[13],"deployment":[14],"challenges":[15,123],"for":[16,143,176,222],"Vision":[17],"Transformers":[18],"(ViTs)":[19],"in":[20,26,279],"practical":[21],"applications.":[22],"Despite":[23],"recent":[24],"advancements":[25],"pruning":[28],"reduction":[31],"techniques":[32,156],"speed":[33,37],"up":[34,200],"the":[35,50,119,162,182,275],"inference":[36,109,236],"of":[38,161,260,277,289],"ViTs,":[39],"these":[40,83],"approaches":[41],"either":[42],"adopt":[43],"a":[44,91,102,112,152,173,189,213,228,239],"fixed":[45],"sparsity":[46],"ratio":[47],"or":[48],"overlook":[49],"meaningful":[51],"interplay":[52],"between":[53],"architectural":[54,116,126,177],"optimization":[55,191,262],"selection.":[58],"Consequently,":[59],"this":[60,148,209],"static":[61],"single-dimension":[63],"compression":[64,73],"often":[65],"leads":[66],"to":[67,78,106,124,157,201],"pronounced":[68],"accuracy":[69],"degradation":[70],"under":[71],"aggressive":[72],"rates,":[74],"as":[75,172,238,265],"they":[76,137],"fail":[77],"fully":[79],"explore":[80],"redundancies":[81],"across":[82],"two":[84],"orthogonal":[85],"dimensions.":[86],"Therefore,":[87],"we":[88,150,211,226],"introduce":[89,227],"PRANCE,":[90],"framework":[92,121,255],"which":[93],"can":[94],"jointly":[95],"optimize":[96],"activated":[97],"channels":[98,160],"tokens":[100,290],"on":[101],"per-sample":[103],"basis,":[104],"aiming":[105],"accelerate":[107],"ViTs'":[108,235],"process":[110,237],"from":[111],"unified":[113],"data":[114,187],"perspective.":[117],"However,":[118],"joint":[120],"poses":[122],"both":[125],"decision-making":[128],"aspects.":[129],"First,":[130],"while":[131,291],"ViTs":[132],"inherently":[133],"support":[134,158],"variable-token":[135],"inference,":[136],"do":[138],"not":[139],"facilitate":[140],"dynamic":[141],"computations":[142],"variable":[144],"channels.":[145],"To":[146,208],"overcome":[147],"limitation,":[149],"propose":[151],"meta-network":[153],"using":[154],"weight-sharing":[155],"arbitrary":[159],"Multi-Head":[163],"Self-Attention":[164],"(MHSA)":[165],"Multi-Layer":[167],"Perceptron":[168],"(MLP)":[169],"layers,":[170],"serving":[171],"foundational":[174],"decision-making.":[178,224],"Second,":[179],"simultaneously":[180,256],"optimizing":[181],"structure":[184],"input":[186],"constitutes":[188],"combinatorial":[190],"problem":[192],"an":[194],"extremely":[195],"large":[196],"decision":[197,241],"space,":[198],"reaching":[199],"around":[202],"$10^{14}$1014,":[203],"making":[204],"supervised":[205],"learning":[206],"infeasible.":[207],"end,":[210],"design":[212],"lightweight":[214],"selector":[215],"employing":[216],"Proximal":[217],"Policy":[218],"Optimization":[219],"algorithm":[220],"(PPO)":[221],"efficient":[223],"Furthermore,":[225],"novel":[229],"\"Result-to-Go\"":[230],"training":[231],"mechanism":[232],"that":[233],"models":[234],"Markov":[240],"process,":[242],"significantly":[243],"reducing":[244,280],"action":[245],"space":[246],"mitigating":[248],"delayed-reward":[249],"issues":[250],"during":[251],"training.":[252],"Additionally,":[253],"our":[254],"supports":[257],"different":[258],"kinds":[259],"methods":[263],"such":[264],"pruning,":[266],"merging,":[267],"sequential":[269],"pruning-merging":[270],"strategies.":[271],"Extensive":[272],"experiments":[273],"demonstrate":[274],"effectiveness":[276],"PRANCE":[278],"FLOPs":[281],"by":[282],"approximately":[283],"50%,":[284],"retaining":[285],"only":[286],"about":[287],"10%":[288],"achieving":[292],"lossless":[293],"Top-1":[294],"accuracy.":[295]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
