{"id":"https://openalex.org/W4392677686","doi":"https://doi.org/10.48550/arxiv.2403.04866","title":"A Modular End-to-End Multimodal Learning Method for Structured and\n Unstructured Data","display_name":"A Modular End-to-End Multimodal Learning Method for Structured and\n Unstructured Data","publication_year":2024,"publication_date":"2024-03-07","ids":{"openalex":"https://openalex.org/W4392677686","doi":"https://doi.org/10.48550/arxiv.2403.04866"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2403.04866","pdf_url":"https://arxiv.org/pdf/2403.04866","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2403.04866","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034150908","display_name":"Marco D Alessandro","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alessandro, Marco D","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052159647","display_name":"Enrique Calabr\u00e9s","orcid":"https://orcid.org/0009-0005-9803-3998"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Calabr\u00e9s, Enrique","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5072861611","display_name":"Mikel Elkano","orcid":"https://orcid.org/0000-0001-7261-7868"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elkano, Mikel","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":84},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.2505,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.2505,"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":0.2307,"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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.2161,"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/end-to-end-principle","display_name":"End-to-end principle","score":0.53566754},{"id":"https://openalex.org/keywords/unstructured-data","display_name":"Unstructured data","score":0.4258566}],"concepts":[{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.72454435},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6385135},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.53566754},{"id":"https://openalex.org/C2781252014","wikidata":"https://www.wikidata.org/wiki/Q1141900","display_name":"Unstructured data","level":3,"score":0.4258566},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31669587},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.20863423},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.13800195},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.072814584}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2403.04866","pdf_url":"https://arxiv.org/pdf/2403.04866","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2403.04866","pdf_url":"https://arxiv.org/pdf/2403.04866","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3203889067","https://openalex.org/W3184725726","https://openalex.org/W3179968364","https://openalex.org/W2759357633","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2378793138","https://openalex.org/W2376932109","https://openalex.org/W2358668433","https://openalex.org/W1999612375"],"abstract_inverted_index":{"Multimodal":[0],"learning":[1,72],"is":[2,86],"a":[3,68],"rapidly":[4],"growing":[5],"research":[6,21],"field":[7],"that":[8],"has":[9,22,44],"revolutionized":[10],"multitasking":[11],"and":[12,82,98],"generative":[13],"modeling":[14],"in":[15],"AI.":[16],"While":[17],"much":[18],"of":[19,61],"the":[20],"focused":[23],"on":[24],"dealing":[25],"with":[26],"unstructured":[27,83],"data":[28,36],"(e.g.,":[29,37],"language,":[30],"images,":[31],"audio,":[32],"or":[33,42,54],"video),":[34],"structured":[35,81],"tabular":[38],"data,":[39],"time":[40],"series,":[41],"signals)":[43],"received":[45],"less":[46],"attention.":[47],"However,":[48],"many":[49],"industry-relevant":[50],"use":[51],"cases":[52],"involve":[53],"can":[55,77],"be":[56],"benefited":[57],"from":[58,101],"both":[59,80],"types":[60],"data.":[62,84],"In":[63],"this":[64],"work,":[65],"we":[66],"propose":[67],"modular,":[69],"end-to-end":[70],"multimodal":[71],"method":[73],"called":[74],"MAGNUM,":[75],"which":[76],"natively":[78],"handle":[79],"MAGNUM":[85],"flexible":[87],"enough":[88],"to":[89,95],"employ":[90],"any":[91],"specialized":[92],"unimodal":[93],"module":[94],"extract,":[96],"compress,":[97],"fuse":[99],"information":[100],"all":[102],"available":[103],"modalities.":[104]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4392677686","counts_by_year":[],"updated_date":"2024-12-14T13:28:48.333686","created_date":"2024-03-13"}