{"id":"https://openalex.org/W4387968071","doi":"https://doi.org/10.1145/3581783.3611758","title":"Reservoir Computing Transformer for Image-Text Retrieval","display_name":"Reservoir Computing Transformer for Image-Text Retrieval","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4387968071","doi":"https://doi.org/10.1145/3581783.3611758"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3611758","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611758","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","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/A5046442204","display_name":"Wenrui Li","orcid":"https://orcid.org/0000-0002-2393-9016"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenrui Li","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-2393-9016","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079107646","display_name":"Zhengyu Ma","orcid":"https://orcid.org/0000-0003-0799-440X"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyu Ma","raw_affiliation_strings":["Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-0799-440X","affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088224232","display_name":"Liang-Jian Deng","orcid":"https://orcid.org/0000-0003-3178-9772"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang-Jian Deng","raw_affiliation_strings":["University of Electronic Science and Technology of China, Sichuan, China"],"raw_orcid":"https://orcid.org/0000-0003-3178-9772","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033038967","display_name":"Penghong Wang","orcid":"https://orcid.org/0000-0002-5401-5676"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Penghong Wang","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-5401-5676","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062607701","display_name":"Jinqiao Shi","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":"Jinqiao Shi","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0111-1023","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079412089","display_name":"Xiaopeng Fan","orcid":"https://orcid.org/0000-0002-9660-3636"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaopeng Fan","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-9660-3636","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5605","last_page":"5613"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","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"}},"topics":[{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.9889000058174133,"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":0.7988338470458984},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.673385500907898},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5672517418861389},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.493194043636322},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4401710331439972},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33765748143196106},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.32659709453582764},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32261747121810913},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10499939322471619}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7988338470458984},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.673385500907898},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5672517418861389},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.493194043636322},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4401710331439972},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33765748143196106},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.32659709453582764},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32261747121810913},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10499939322471619},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581783.3611758","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611758","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6558088433","display_name":null,"funder_award_id":"U22B2035, 62272128, 62206141, 62236009 and 12271083","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"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W758960492","https://openalex.org/W1905882502","https://openalex.org/W2032480650","https://openalex.org/W2054217036","https://openalex.org/W2103179919","https://openalex.org/W2118706537","https://openalex.org/W2185175083","https://openalex.org/W2272508502","https://openalex.org/W2399419866","https://openalex.org/W2560730294","https://openalex.org/W2745461083","https://openalex.org/W2747853580","https://openalex.org/W2770387316","https://openalex.org/W2786585376","https://openalex.org/W2805693781","https://openalex.org/W2896457183","https://openalex.org/W2897135094","https://openalex.org/W2962964995","https://openalex.org/W2963040148","https://openalex.org/W2964935470","https://openalex.org/W2966715458","https://openalex.org/W2969876226","https://openalex.org/W2981586349","https://openalex.org/W2988823324","https://openalex.org/W2990571534","https://openalex.org/W2997842110","https://openalex.org/W3001555892","https://openalex.org/W3003262368","https://openalex.org/W3014611590","https://openalex.org/W3023742835","https://openalex.org/W3035552787","https://openalex.org/W3037773948","https://openalex.org/W3038427506","https://openalex.org/W3038649929","https://openalex.org/W3090449556","https://openalex.org/W3092820619","https://openalex.org/W3118694826","https://openalex.org/W3155230099","https://openalex.org/W3170977978","https://openalex.org/W3201645700","https://openalex.org/W3213100861","https://openalex.org/W4206477614","https://openalex.org/W4213348104","https://openalex.org/W4214819138","https://openalex.org/W4225329158","https://openalex.org/W4283805294","https://openalex.org/W4285118104","https://openalex.org/W4293518982","https://openalex.org/W4304091674","https://openalex.org/W4309764765","https://openalex.org/W4313126997","https://openalex.org/W4313129750","https://openalex.org/W4313136445","https://openalex.org/W4313477296","https://openalex.org/W4322576838","https://openalex.org/W4386453567","https://openalex.org/W6639102338","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W2770593030","https://openalex.org/W3154990682","https://openalex.org/W2560201613","https://openalex.org/W2171975302","https://openalex.org/W2022352247","https://openalex.org/W4312219546","https://openalex.org/W2377538627","https://openalex.org/W2107220315","https://openalex.org/W2154044472","https://openalex.org/W4210772589"],"abstract_inverted_index":{"Although":[0],"the":[1,89,114,121,126,129,144,147,176],"attention":[2],"mechanism":[3],"in":[4,9,92,139,146,180],"transformers":[5],"has":[6,159],"proven":[7],"successful":[8],"image-text":[10,45],"retrieval":[11],"tasks,":[12],"most":[13],"transformer":[14],"models":[15],"suffer":[16],"from":[17],"a":[18,36,51,74,93,160],"large":[19],"number":[20],"of":[21,62,128,137,155,178,182],"parameters.":[22],"Inspired":[23],"by":[24,120],"brain":[25],"circuits":[26],"that":[27,152],"process":[28],"information":[29],"with":[30,84],"recurrent":[31],"connected":[32],"neurons,":[33],"we":[34,67,142],"propose":[35],"novel":[37],"Reservoir":[38],"Computing":[39],"Transformer":[40],"Reasoning":[41],"Network":[42],"(RCTRN)":[43],"for":[44],"retrieval.":[46],"The":[47,97],"proposed":[48,102],"RCTRN":[49,179],"employs":[50],"two-step":[52],"strategy":[53],"to":[54,103,188],"focus":[55],"on":[56,168],"feature":[57,82],"representation":[58],"and":[59,70,87,112,133,173,184],"data":[60,115,156],"distribution":[61,116],"different":[63,110],"modalities":[64],"respectively.":[65],"Specifically,":[66],"send":[68],"visual":[69],"textual":[71],"features":[72,108],"through":[73],"unified":[75,122],"meshed":[76],"reasoning":[77,99],"module,":[78],"which":[79],"encodes":[80],"multi-level":[81],"relationships":[83],"prior":[85],"knowledge":[86],"aggregates":[88],"complementary":[90],"outputs":[91],"more":[94],"effective":[95],"way.":[96],"reservoir":[98],"network":[100],"is":[101],"optimize":[104],"memory":[105],"connections":[106],"between":[107],"at":[109],"stages":[111],"address":[113],"mismatch":[117],"problem":[118],"introduced":[119],"scheme.":[123],"To":[124],"investigate":[125],"significance":[127],"low":[130,134],"power":[131],"dissipation":[132,186],"bandwidth":[135],"characteristics":[136],"RRN":[138],"practical":[140],"scenarios,":[141],"deployed":[143],"model":[145],"wireless":[148],"transmission":[149],"system,":[150],"demonstrating":[151],"RRN's":[153],"optimization":[154],"structures":[157],"also":[158],"certain":[161],"robustness":[162],"against":[163],"channel":[164],"noise.":[165],"Extensive":[166],"experiments":[167],"two":[169],"benchmark":[170],"datasets,":[171],"Flickr30K":[172],"MS-COCO,":[174],"demonstrate":[175],"superiority":[177],"terms":[181],"performance":[183],"low-power":[185],"compared":[187],"state-of-the-art":[189],"baselines.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}