{"id":"https://openalex.org/W4408353907","doi":"https://doi.org/10.1109/icassp49660.2025.10889859","title":"GSMM: Efficient Global Sparsification for Resource-Conscious Multimodal Models","display_name":"GSMM: Efficient Global Sparsification for Resource-Conscious Multimodal Models","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408353907","doi":"https://doi.org/10.1109/icassp49660.2025.10889859"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10889859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889859","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"https://openalex.org/A5042533176","display_name":"Wenlun Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Wenlun Zhang","raw_affiliation_strings":["Keio University"],"affiliations":[{"raw_affiliation_string":"Keio University","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050387621","display_name":"Haoran Pang","orcid":"https://orcid.org/0000-0003-1604-5011"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Haoran Pang","raw_affiliation_strings":["Keio University"],"affiliations":[{"raw_affiliation_string":"Keio University","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102104562","display_name":"Yucai Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I4399598377","display_name":"Institute of Science and Technology","ror":"https://ror.org/02wxm3f24","country_code":null,"type":"education","lineage":["https://openalex.org/I155028946","https://openalex.org/I4399598377"]},{"id":"https://openalex.org/I32820368","display_name":"Guangdong Polytechnic of Science and Technology","ror":"https://ror.org/01wq2p249","country_code":"CN","type":"education","lineage":["https://openalex.org/I32820368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yucai Zhou","raw_affiliation_strings":["Guangzhou Institute of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Guangzhou Institute of Science and Technology","institution_ids":["https://openalex.org/I32820368","https://openalex.org/I4399598377"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104265585","display_name":"Shixiao Wang","orcid":"https://orcid.org/0009-0006-0581-2632"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shixiao Wang","raw_affiliation_strings":["University of Birmingham"],"affiliations":[{"raw_affiliation_string":"University of Birmingham","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069449575","display_name":"L. Li","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Luking Li","raw_affiliation_strings":["Keio University"],"affiliations":[{"raw_affiliation_string":"Keio University","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5042533176"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02053193,"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":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.8921999931335449,"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/T12031","display_name":"Speech and dialogue systems","score":0.8921999931335449,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.8870999813079834,"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/T10320","display_name":"Neural Networks and Applications","score":0.8238000273704529,"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":0.7115418910980225},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.44097229838371277},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3433232307434082},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.13318318128585815}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7115418910980225},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.44097229838371277},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3433232307434082},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.13318318128585815}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10889859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889859","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W2560730294","https://openalex.org/W2808133870","https://openalex.org/W2979382951","https://openalex.org/W3162847008","https://openalex.org/W4226396876","https://openalex.org/W4312590184","https://openalex.org/W4312717156","https://openalex.org/W4312767675","https://openalex.org/W4386071640","https://openalex.org/W4389523832","https://openalex.org/W4390874023","https://openalex.org/W4393156341","https://openalex.org/W4393160450","https://openalex.org/W4393160566","https://openalex.org/W4402727764","https://openalex.org/W4403081466","https://openalex.org/W4403878467","https://openalex.org/W4403878569","https://openalex.org/W4403878655","https://openalex.org/W4409347105","https://openalex.org/W6745148473","https://openalex.org/W6791279787","https://openalex.org/W6796581206","https://openalex.org/W6809995052","https://openalex.org/W6839677739","https://openalex.org/W6843405348","https://openalex.org/W6848451824","https://openalex.org/W6848948516","https://openalex.org/W6851592950","https://openalex.org/W6851950068","https://openalex.org/W6852534536","https://openalex.org/W6852962002","https://openalex.org/W6854094408","https://openalex.org/W6854347851","https://openalex.org/W6854866820","https://openalex.org/W6857251794","https://openalex.org/W6860959834","https://openalex.org/W6862364835","https://openalex.org/W6869468661","https://openalex.org/W6872157027","https://openalex.org/W6872716837","https://openalex.org/W7046576797","https://openalex.org/W7048135330","https://openalex.org/W7065502145"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Large":[0],"Multimodal":[1],"Models":[2],"(LMMs)":[3],"are":[4],"increasingly":[5],"essential":[6],"in":[7,117],"various":[8],"real-time":[9],"applications,":[10],"yet":[11],"their":[12],"substantial":[13],"parameter":[14],"counts":[15],"and":[16,135],"complex":[17],"architectures":[18],"pose":[19],"significant":[20],"challenges.":[21],"Traditional":[22],"global":[23,53,96,108,115],"compression":[24],"methods":[25],"often":[26],"rely":[27],"on":[28,80,129],"trial-and-error":[29],"experimentation,":[30],"leading":[31],"to":[32,93,105,159],"inefficiencies.":[33],"In":[34],"this":[35],"paper,":[36],"we":[37,87],"introduce":[38],"new":[39,147],"GS-MM,":[40],"an":[41],"Efficient":[42],"Global":[43],"Sparsification":[44],"technique":[45],"tailored":[46],"for":[47,149],"resource-conscious":[48],"multimodal":[49,91],"models.":[50],"GS-MM":[51],"assigns":[52],"sparsification":[54],"strategies":[55],"by":[56],"extracting":[57],"primitive":[58],"importance":[59,68,92,97],"from":[60,71],"the":[61,67,72,81,84,89,107,112,121],"model\u2019s":[62],"components.":[63],"We":[64,119],"first":[65],"derive":[66],"of":[69,75,83,114,123],"elements":[70],"mapping":[73],"values":[74],"fully":[76],"weighted":[77],"activations,":[78],"based":[79],"weights":[82],"elements.":[85],"Subsequently,":[86],"compute":[88],"average":[90],"establish":[94],"a":[95],"score.":[98],"This":[99],"score":[100],"is":[101],"then":[102],"linearly":[103],"mapped":[104],"determine":[106],"allocation":[109],"ratio,":[110],"enabling":[111],"realization":[113],"sparsity":[116,161],"LMMs.":[118],"demonstrate":[120],"effectiveness":[122],"our":[124,154],"approach":[125,155],"through":[126],"extensive":[127],"experiments":[128],"diverse":[130],"benchmarks,":[131],"including":[132],"visual":[133],"question-answering":[134],"reasoning":[136],"tasks.":[137],"Our":[138],"pruned":[139],"models":[140],"consistently":[141],"outperform":[142],"conventional":[143],"pruning":[144],"methods,":[145],"setting":[146],"standards":[148],"compressed":[150],"model":[151,164],"performance.":[152],"Notably,":[153],"exhibits":[156],"remarkable":[157],"resilience":[158],"increasing":[160],"ratios,":[162],"preserving":[163],"quality":[165],"even":[166],"under":[167],"extreme":[168],"compression.":[169]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}