{"id":"https://openalex.org/W4386598348","doi":"https://doi.org/10.1109/icip49359.2023.10223170","title":"Atten-Adapter: A Unified Attention-Based Adapter for Efficient Tuning","display_name":"Atten-Adapter: A Unified Attention-Based Adapter for Efficient Tuning","publication_year":2023,"publication_date":"2023-09-11","ids":{"openalex":"https://openalex.org/W4386598348","doi":"https://doi.org/10.1109/icip49359.2023.10223170"},"language":"en","primary_location":{"id":"doi:10.1109/icip49359.2023.10223170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip49359.2023.10223170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Image Processing (ICIP)","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/A5100711421","display_name":"Kaiwen Li","orcid":"https://orcid.org/0000-0003-1550-5987"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiwen Li","raw_affiliation_strings":["Xi’an Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102487300","display_name":"Wenzhe Gu","orcid":"https://orcid.org/0000-0002-9557-6672"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzhe Gu","raw_affiliation_strings":["Xi’an Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101242973","display_name":"Maixuan Xue","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maixuan Xue","raw_affiliation_strings":["Xi’an Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011475525","display_name":"Jiahua Xiao","orcid":"https://orcid.org/0000-0002-0469-528X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahua Xiao","raw_affiliation_strings":["Xi’an Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028539573","display_name":"Dahu Shi","orcid":"https://orcid.org/0000-0002-8844-8808"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dahu Shi","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040886197","display_name":"Xing Wei","orcid":"https://orcid.org/0000-0002-5025-3941"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Wei","raw_affiliation_strings":["Xi’an Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4491,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.64020378,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1265","last_page":"1269"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9997000098228455,"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/adapter","display_name":"Adapter (computing)","score":0.9470668435096741},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7573167085647583},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5509141087532043},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5214687585830688},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.5128145813941956},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.23618608713150024},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12027162313461304}],"concepts":[{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.9470668435096741},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7573167085647583},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5509141087532043},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5214687585830688},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.5128145813941956},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.23618608713150024},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12027162313461304},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip49359.2023.10223170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip49359.2023.10223170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2507296351","https://openalex.org/W2963703197","https://openalex.org/W3138516171","https://openalex.org/W3145450063","https://openalex.org/W3151130473","https://openalex.org/W3154043262","https://openalex.org/W3168867926","https://openalex.org/W3170841864","https://openalex.org/W3174770825","https://openalex.org/W3175604467","https://openalex.org/W3176828726","https://openalex.org/W3198377975","https://openalex.org/W4312351187","https://openalex.org/W4312651322","https://openalex.org/W6739901393","https://openalex.org/W6759579507","https://openalex.org/W6784333009","https://openalex.org/W6785440099","https://openalex.org/W6791353385","https://openalex.org/W6796581206","https://openalex.org/W6802744804","https://openalex.org/W6838701581"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2045049461","https://openalex.org/W1978893398","https://openalex.org/W2201908702","https://openalex.org/W4381094582","https://openalex.org/W2369625323","https://openalex.org/W2364579609","https://openalex.org/W1977906818"],"abstract_inverted_index":{"Recently,":[0],"more":[1,3,83],"and":[2,29,81,112,120],"large":[4],"pre-trained":[5,23],"models":[6,24,108],"have":[7,13],"emerged.":[8],"Several":[9],"parameter-efficient":[10],"tuning":[11],"methods":[12],"been":[14],"studied":[15],"to":[16,25,85,90,103,149],"transfer":[17],"the":[18,22,44,51,61,65,68,86,91,125,150],"prior":[19],"knowledge":[20],"of":[21,46,64,70,106,127,140],"specific":[26],"downstream":[27],"tasks":[28,117],"achieve":[30],"promising":[31],"results.":[32],"This":[33],"paper":[34],"proposes":[35],"a":[36,95],"simple":[37],"yet":[38],"effective":[39],"method":[40,144],"called":[41],"Atten-Adapter.":[42],"To":[43],"best":[45],"our":[47,128,143],"knowledge,":[48],"this":[49],"is":[50],"first":[52],"work":[53],"that":[54],"utilizes":[55],"attention":[56,84],"with":[57],"learnable":[58],"parameters":[59],"as":[60,110],"internal":[62],"structure":[63],"adapter":[66,74],"in":[67,115],"field":[69],"fine-tuning.":[71],"The":[72],"attention-based":[73],"can":[75,99],"provide":[76],"better":[77],"information":[78],"fusion":[79],"ability":[80],"pay":[82],"global":[87],"features":[88],"compared":[89,148],"MLP-based":[92],"adapter.":[93],"As":[94],"plug-and-play":[96],"module,":[97],"Atten-Adapter":[98],"be":[100],"easily":[101],"adapted":[102],"different":[104,116],"types":[105],"vision":[107],"such":[109],"ConvNets":[111],"Transformer":[113],"architectures":[114],"like":[118],"classification":[119],"segmentation.":[121],"Moreover,":[122],"we":[123],"demonstrate":[124],"generality":[126],"proposed":[129],"adapters":[130],"by":[131],"conducting":[132],"experiments":[133],"on":[134],"language":[135],"models.":[136],"With":[137],"small":[138],"amounts":[139],"tunable":[141],"parameters,":[142],"achieves":[145],"significant":[146],"improvements":[147],"previous":[151],"state-of-the-art":[152],"methods.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}