{"id":"https://openalex.org/W4304080256","doi":"https://doi.org/10.1145/3503161.3548757","title":"Multi-modal Learning Algorithms and Network Architectures for Information Extraction and Retrieval","display_name":"Multi-modal Learning Algorithms and Network Architectures for Information Extraction and Retrieval","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304080256","doi":"https://doi.org/10.1145/3503161.3548757"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548757","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548757","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","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/A5056994081","display_name":"Maurits Bleeker","orcid":null},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]},{"id":"https://openalex.org/I4210135670","display_name":"Amsterdam University of the Arts","ror":"https://ror.org/04dde1554","country_code":"NL","type":"education","lineage":["https://openalex.org/I4210135670"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Maurits Bleeker","raw_affiliation_strings":["University of Amsterdam, Amsterdam, Netherlands"],"affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5056994081"],"corresponding_institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09275631,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6925","last_page":"6929"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"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":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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":0.996399998664856,"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":0.8281562924385071},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6312695741653442},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6248217225074768},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5747745037078857},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5326069593429565},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5108668208122253},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.4992101192474365},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.48169073462486267},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47948774695396423},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.46447765827178955},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45712369680404663},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4417068660259247},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4212014079093933},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4154585301876068},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32170242071151733}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8281562924385071},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6312695741653442},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6248217225074768},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5747745037078857},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5326069593429565},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5108668208122253},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.4992101192474365},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.48169073462486267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47948774695396423},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.46447765827178955},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45712369680404663},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4417068660259247},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4212014079093933},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4154585301876068},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32170242071151733},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503161.3548757","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548757","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W251438302","https://openalex.org/W1861492603","https://openalex.org/W2096733369","https://openalex.org/W2185175083","https://openalex.org/W2560835477","https://openalex.org/W2740767790","https://openalex.org/W2810983211","https://openalex.org/W2962964995","https://openalex.org/W2988823324","https://openalex.org/W2994818707","https://openalex.org/W3035454331","https://openalex.org/W3035605030","https://openalex.org/W3090449556","https://openalex.org/W3108373531","https://openalex.org/W3109485382","https://openalex.org/W3109684201","https://openalex.org/W3118694826","https://openalex.org/W3135367836","https://openalex.org/W3154430790","https://openalex.org/W3160179442","https://openalex.org/W4226211003","https://openalex.org/W4301104990"],"related_works":["https://openalex.org/W2237537322","https://openalex.org/W2950678851","https://openalex.org/W4301248618","https://openalex.org/W2165343651","https://openalex.org/W2242427765","https://openalex.org/W2075830955","https://openalex.org/W2343790552","https://openalex.org/W4309346246","https://openalex.org/W3111398917","https://openalex.org/W4385507578"],"abstract_inverted_index":{"Large-scale":[0],"(pre-)training":[1],"has":[2],"recently":[3],"achieved":[4],"great":[5],"success":[6],"on":[7,56,90,115],"both":[8,25],"uni-":[9],"and":[10,31,50,60],"multi-modal":[11,45],"downstream":[12],"evaluation":[13],"tasks.":[14],"However,":[15],"this":[16],"training":[17],"paradigm":[18],"generally":[19],"comes":[20],"with":[21,52],"a":[22,73,131,147],"high":[23],"cost,":[24],"in":[26,102,146],"the":[27,42,53,65,81,91,99,103,109,116,122,143],"amount":[28],"of":[29,44,118],"compute":[30],"data":[32],"needed":[33],"for":[34,47,77,80,121],"training.":[35],"In":[36],"my":[37],"Ph.D.":[38],"thesis,":[39],"I":[40,71,88,96,113,125],"study":[41],"problem":[43],"learning":[46,58,66,105,120,134,140],"information":[48],"extraction":[49],"retrieval,":[51],"main":[54],"focus":[55,89,114],"new":[57],"algorithms":[59],"network":[61,75],"architectures":[62],"to":[63,108],"make":[64],"process":[67],"more":[68],"efficient.":[69],"First,":[70],"introduce":[72,126],"novel":[74,132],"architecture":[76],"bidirectional":[78],"decoding":[79,129,142],"scene":[82],"text":[83],"recognition":[84],"(STR)":[85],"task.":[86,95,111,124],"Next,":[87],"image-caption":[92],"retrieval":[93],"(ICR)":[94],"question":[97],"if":[98],"results":[100],"obtained":[101],"metric":[104],"field":[106],"generalize":[107],"ICR":[110,123],"Finally,":[112],"reduction":[117],"shortcut":[119,138],"latent":[127,149],"target":[128],"(LTD),":[130],"constraint-based":[133],"algorithm":[135],"which":[136],"reduces":[137],"feature":[139],"by":[141],"input":[144],"caption":[145],"semantic":[148],"space.":[150]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
