{"id":"https://openalex.org/W7105696030","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228409","title":"RL-Pruner: Retraining-Free Global Exploration Pruning Method Based on Reinforcement Learning","display_name":"RL-Pruner: Retraining-Free Global Exploration Pruning Method Based on Reinforcement Learning","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W7105696030","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228409"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228409","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228409","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":null,"display_name":"Guangzhen Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guangzhen Yao","raw_affiliation_strings":["Northeast Normal University"],"affiliations":[{"raw_affiliation_string":"Northeast Normal University","institution_ids":["https://openalex.org/I184983240"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yi Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I2803050950","display_name":"Danish Ministry of Defence","ror":"https://ror.org/02ncgfj77","country_code":"DK","type":"government","lineage":["https://openalex.org/I2803050950"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Yi Wang","raw_affiliation_strings":["Modale AI Sci-Tech"],"affiliations":[{"raw_affiliation_string":"Modale AI Sci-Tech","institution_ids":["https://openalex.org/I2803050950"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenxin Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxin Zhang","raw_affiliation_strings":["University of Chinese Academy of Science"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Science","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xaioyu Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I922845939","display_name":"Philadelphia University","ror":"https://ror.org/03zzmyz63","country_code":"US","type":"education","lineage":["https://openalex.org/I922845939"]},{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xaioyu Deng","raw_affiliation_strings":["University of Pennsylvania Philadelphia"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania Philadelphia","institution_ids":["https://openalex.org/I922845939","https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chengze Du","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengze Du","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Renda Han","orcid":null},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renda Han","raw_affiliation_strings":["Hainan University"],"affiliations":[{"raw_affiliation_string":"Hainan University","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhanghao Qin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhanghao Qin","raw_affiliation_strings":["Nanyang Technology University"],"affiliations":[{"raw_affiliation_string":"Nanyang Technology University","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I75900474","display_name":"Hubei University","ror":"https://ror.org/03a60m280","country_code":"CN","type":"education","lineage":["https://openalex.org/I75900474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Li","raw_affiliation_strings":["Hubei University"],"affiliations":[{"raw_affiliation_string":"Hubei University","institution_ids":["https://openalex.org/I75900474"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bobin Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bobin Xie","raw_affiliation_strings":["Shanghai University of Electric Power"],"affiliations":[{"raw_affiliation_string":"Shanghai University of Electric Power","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bowen Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Dong","raw_affiliation_strings":["Tianjin University"],"affiliations":[{"raw_affiliation_string":"Tianjin University","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Haiming Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiming Peng","raw_affiliation_strings":["Fudan University"],"affiliations":[{"raw_affiliation_string":"Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sandong Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sandong Zhu","raw_affiliation_strings":["Northeast Normal University"],"affiliations":[{"raw_affiliation_string":"Northeast Normal University","institution_ids":["https://openalex.org/I184983240"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Long Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Zhang","raw_affiliation_strings":["Northeast Normal University"],"affiliations":[{"raw_affiliation_string":"Northeast Normal University","institution_ids":["https://openalex.org/I184983240"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zezhou Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zezhou Wang","raw_affiliation_strings":["The Australian National University"],"affiliations":[{"raw_affiliation_string":"The Australian National University","institution_ids":["https://openalex.org/I118347636"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zeyu Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zeyu Zhang","raw_affiliation_strings":["The Australian National University"],"affiliations":[{"raw_affiliation_string":"The Australian National University","institution_ids":["https://openalex.org/I118347636"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":15,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I184983240"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.57592388,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.311599999666214,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.311599999666214,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.13410000503063202,"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/T10028","display_name":"Topic Modeling","score":0.13089999556541443,"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/pruning","display_name":"Pruning","score":0.8026000261306763},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5976999998092651},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.49050000309944153},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4869999885559082},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.484499990940094},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.454800009727478},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.4081999957561493},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3865000009536743}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8026000261306763},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7285000085830688},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5976999998092651},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5284000039100647},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5006999969482422},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.49050000309944153},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4869999885559082},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.454800009727478},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.4081999957561493},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3865000009536743},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32589998841285706},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C164752517","wikidata":"https://www.wikidata.org/wiki/Q5570875","display_name":"Global optimization","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.27720001339912415},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.26460000872612},{"id":"https://openalex.org/C2776985865","wikidata":"https://www.wikidata.org/wiki/Q26820931","display_name":"Reducer","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228409","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228409","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2963323070","https://openalex.org/W2963748441","https://openalex.org/W2979691890","https://openalex.org/W3106070274","https://openalex.org/W3136363192","https://openalex.org/W3174657338","https://openalex.org/W4393160524","https://openalex.org/W4394625583","https://openalex.org/W4395957348","https://openalex.org/W4404783751","https://openalex.org/W4406859087"],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1,66],"models":[2,153],"(LLMs)":[3],"have":[4],"achieved":[5],"significant":[6],"success":[7],"in":[8,53,64],"complex":[9],"tasks":[10],"across":[11],"various":[12],"domains,":[13],"but":[14],"these":[15,56],"achievements":[16],"come":[17],"with":[18,181],"high":[19],"computational":[20],"costs":[21],"and":[22,43,113,133,151,157],"long":[23],"inference":[24],"delays.":[25],"Pruning,":[26],"as":[27],"an":[28],"effective":[29],"optimization":[30],"technique,":[31],"simplifies":[32],"model":[33,41,80],"structures":[34],"by":[35,190],"removing":[36],"redundant":[37],"components,":[38],"thereby":[39],"improving":[40],"generalization":[42],"operational":[44],"efficiency.":[45],"Although":[46],"existing":[47,182],"pruning":[48,54,92,183],"retraining-free":[49,90,184],"algorithms":[50,57],"perform":[51],"excellently":[52],"time,":[55],"often":[58],"focus":[59],"on":[60,107,154,169],"local":[61],"optimal":[62,73,138],"solutions":[63],"encoder-based":[65],"models,":[67],"lacking":[68],"comprehensive":[69],"exploration":[70],"of":[71,99,130],"global":[72,137],"solutions,":[74],"which":[75],"may":[76],"affect":[77],"the":[78,103,114,127,136,155,170,186],"overall":[79],"performance.":[81],"To":[82],"address":[83],"this":[84,145],"issue,":[85],"we":[86],"propose":[87],"a":[88,176],"novel":[89],"structured":[91],"algorithm,":[93],"named":[94],"RL-Pruner.":[95],"The":[96],"algorithm":[97],"consists":[98],"two":[100],"main":[101],"stages:":[102],"Mask":[104,119],"Rearrangement":[105],"Based":[106],"Asynchronous":[108],"Advantage":[109],"Actor-Critic":[110],"(MA3C)":[111],"stage":[112],"BiConjugate":[115],"Gradient":[116],"Solver":[117],"for":[118],"Tuning":[120],"(BGMT)":[121],"stage.":[122],"It":[123],"aims":[124],"to":[125],"explore":[126],"intra-layer":[128],"interactions":[129],"mask":[131],"variables":[132],"efficiently":[134],"find":[135],"solution":[139],"without":[140],"requiring":[141],"retraining.":[142],"We":[143],"evaluate":[144],"method":[146],"using":[147],"BERT<inf":[148],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[149,172],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">BASE</inf>":[150],"DistilBERT":[152],"GLUE":[156],"SQuAD":[158],"benchmark":[159],"tests.":[160],"Experimental":[161],"results":[162],"show":[163],"that":[164],"RL-Pruner":[165],"significantly":[166],"improves":[167],"accuracy":[168],"SQuAD<inf":[171],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1.1</inf>":[173],"benchmark.":[174],"Under":[175],"60%":[177],"FLOPs":[178],"constraint,":[179],"compared":[180],"algorithms,":[185],"F1":[187],"score":[188],"increases":[189],"4.25%.":[191]},"counts_by_year":[],"updated_date":"2025-11-15T23:13:30.683059","created_date":"2025-11-14T00:00:00"}