{"id":"https://openalex.org/W4294069431","doi":"https://doi.org/10.1109/icce-taiwan55306.2022.9869252","title":"On Multimodal Semantic Consistency Detection of News Articles with Image Caption Pairs","display_name":"On Multimodal Semantic Consistency Detection of News Articles with Image Caption Pairs","publication_year":2022,"publication_date":"2022-07-06","ids":{"openalex":"https://openalex.org/W4294069431","doi":"https://doi.org/10.1109/icce-taiwan55306.2022.9869252"},"language":"en","primary_location":{"id":"doi:10.1109/icce-taiwan55306.2022.9869252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan55306.2022.9869252","pdf_url":null,"source":{"id":"https://openalex.org/S4363607852","display_name":"2022 IEEE International Conference on Consumer Electronics - Taiwan","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":"2022 IEEE International Conference on Consumer Electronics - Taiwan","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/A5100374346","display_name":"Yuwei Chen","orcid":"https://orcid.org/0000-0003-0148-3609"},"institutions":[{"id":"https://openalex.org/I113508548","display_name":"Albany State University","ror":"https://ror.org/01vme4277","country_code":"US","type":"education","lineage":["https://openalex.org/I113508548"]},{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuwei Chen","raw_affiliation_strings":["University at Albany &#x2013; State University at New York,Albany,NY,USA,12065"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University at Albany &#x2013; State University at New York,Albany,NY,USA,12065","institution_ids":["https://openalex.org/I113508548","https://openalex.org/I392282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012638803","display_name":"Ming\u2010Ching Chang","orcid":"https://orcid.org/0000-0001-9325-5341"},"institutions":[{"id":"https://openalex.org/I113508548","display_name":"Albany State University","ror":"https://ror.org/01vme4277","country_code":"US","type":"education","lineage":["https://openalex.org/I113508548"]},{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming-Ching Chang","raw_affiliation_strings":["University at Albany &#x2013; State University at New York,Albany,NY,USA,12065"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University at Albany &#x2013; State University at New York,Albany,NY,USA,12065","institution_ids":["https://openalex.org/I113508548","https://openalex.org/I392282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1849,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.50789805,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"355","last_page":"356"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning 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/T11714","display_name":"Multimodal Machine Learning 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/T10028","display_name":"Topic Modeling","score":0.9794999957084656,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9545999765396118,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.8554097414016724},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8122467994689941},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.6863915920257568},{"id":"https://openalex.org/keywords/disinformation","display_name":"Disinformation","score":0.5734474658966064},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5638670325279236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5291690826416016},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4631829261779785},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45839107036590576},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.4207627475261688},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.41668978333473206},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.321397602558136},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.12778708338737488},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08987888693809509}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.8554097414016724},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8122467994689941},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.6863915920257568},{"id":"https://openalex.org/C2776552730","wikidata":"https://www.wikidata.org/wiki/Q189656","display_name":"Disinformation","level":3,"score":0.5734474658966064},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5638670325279236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5291690826416016},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4631829261779785},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45839107036590576},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.4207627475261688},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.41668978333473206},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.321397602558136},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.12778708338737488},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08987888693809509},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-taiwan55306.2022.9869252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan55306.2022.9869252","pdf_url":null,"source":{"id":"https://openalex.org/S4363607852","display_name":"2022 IEEE International Conference on Consumer Electronics - Taiwan","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":"2022 IEEE International Conference on Consumer Electronics - Taiwan","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5771177262","display_name":null,"funder_award_id":"HR001120C0123","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1889081078","https://openalex.org/W3091588028","https://openalex.org/W3166396011","https://openalex.org/W3173220247"],"related_works":["https://openalex.org/W4210416330","https://openalex.org/W3043508177","https://openalex.org/W4382752644","https://openalex.org/W4309170162","https://openalex.org/W3049488969","https://openalex.org/W2775506363","https://openalex.org/W3088136942","https://openalex.org/W2043544044","https://openalex.org/W3209170404","https://openalex.org/W4323929292"],"abstract_inverted_index":{"Recently":[0],"multi-modal":[1],"consistency":[2,23,57],"detection":[3],"has":[4],"been":[5],"proposed":[6,61],"as":[7],"method":[8,42,62,79,94],"to":[9,55],"combat":[10],"disinformation.":[11],"However,":[12],"state-of-the-art":[13],"methods":[14,26],"lack":[15],"the":[16,68,110,121,127],"fine":[17],"grained":[18,85],"localized":[19],"evidence":[20,86],"needed":[21],"for":[22],"detection.":[24],"Current":[25],"also":[27],"struggle":[28],"on":[29,95,120],"longer":[30],"texts":[31],"that":[32,43],"are":[33],"present":[34],"in":[35,65],"news":[36,73,107],"articles.":[37],"We":[38,91,115],"propose":[39],"an":[40,117],"ensemble":[41],"combines":[44],"a":[45,96],"series":[46],"of":[47,106,129],"visual":[48],"detectors":[49],"and":[50,72,82,100],"BERT":[51],"based":[52],"NLP":[53],"models":[54],"compute":[56],"between":[58],"modalities.":[59],"The":[60],"is":[63],"effective":[64],"both":[66],"detecting":[67],"standard":[69],"image-caption":[70,98],"pairs":[71],"articles":[74,108],"containing":[75],"multiple":[76],"paragraphs.":[77],"Our":[78],"can":[80],"localize":[81],"provide":[83],"fined":[84],"towards":[87],"its":[88],"given":[89],"responses.":[90],"evaluate":[92],"our":[93,130],"MSCOCO":[97,123],"subset":[99],"image":[101],"&":[102],"text":[103],"inconsistency":[104],"evaluation":[105],"from":[109],"U.S.":[111],"DARPA":[112],"SemaFor":[113],"program.":[114],"achieved":[116],"83%":[118],"AUC":[119],"gathered":[122],"dataset,":[124],"which":[125],"shows":[126],"effectiveness":[128],"method.":[131]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
