{"id":"https://openalex.org/W2798631346","doi":"https://doi.org/10.18653/v1/p18-2074","title":"Do Neural Network Cross-Modal Mappings Really Bridge Modalities?","display_name":"Do Neural Network Cross-Modal Mappings Really Bridge Modalities?","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2798631346","doi":"https://doi.org/10.18653/v1/p18-2074","mag":"2798631346"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p18-2074","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-2074","pdf_url":"https://www.aclweb.org/anthology/P18-2074.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P18-2074.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059014800","display_name":"Guillem Collell","orcid":"https://orcid.org/0000-0003-1998-8621"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Guillem Collell","raw_affiliation_strings":["Department of Computer Science KU Leuven","University of Copenhagen, Copenhagen, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science KU Leuven","institution_ids":[]},{"raw_affiliation_string":"University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075796989","display_name":"Marie\u2010Francine Moens","orcid":"https://orcid.org/0000-0002-3732-9323"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Marie-Francine Moens","raw_affiliation_strings":["Department of Computer Science KU Leuven","University of Copenhagen, Copenhagen, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science KU Leuven","institution_ids":[]},{"raw_affiliation_string":"University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059014800"],"corresponding_institution_ids":["https://openalex.org/I124055696"],"apc_list":null,"apc_paid":null,"fwci":0.14438254,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.41583562,"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":"462","last_page":"468"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9987000226974487,"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":0.9987000226974487,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9980000257492065,"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/T10028","display_name":"Topic Modeling","score":0.9954000115394592,"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":0.7086794376373291},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.6970316171646118},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6592247486114502},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.641593873500824},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.6282824277877808},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5731381177902222},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5519617199897766},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.5250496864318848},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5211822390556335},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4973433315753937},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4414820671081543},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3765590786933899},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3651391863822937},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3313307762145996},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2661510705947876},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.217166930437088}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7086794376373291},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.6970316171646118},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6592247486114502},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.641593873500824},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.6282824277877808},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5731381177902222},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5519617199897766},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.5250496864318848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5211822390556335},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4973433315753937},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4414820671081543},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3765590786933899},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3651391863822937},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3313307762145996},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2661510705947876},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.217166930437088},{"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/p18-2074","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-2074","pdf_url":"https://www.aclweb.org/anthology/P18-2074.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1805.07616","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1805.07616","pdf_url":"https://arxiv.org/pdf/1805.07616","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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2798631346","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1805.07616","pdf_url":null,"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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1805.07616","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1805.07616","pdf_url":null,"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":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.18653/v1/p18-2074","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-2074","pdf_url":"https://www.aclweb.org/anthology/P18-2074.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322308","display_name":"KU Leuven","ror":"https://ror.org/05f950310"},{"id":"https://openalex.org/F4320338463","display_name":"CHIST-ERA","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2798631346.pdf","grobid_xml":"https://content.openalex.org/works/W2798631346.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2963158451","https://openalex.org/W2795389793","https://openalex.org/W3009411434","https://openalex.org/W3185199595","https://openalex.org/W2949904711","https://openalex.org/W3022744764","https://openalex.org/W3025974655","https://openalex.org/W2772313889","https://openalex.org/W2785903172","https://openalex.org/W3022099995","https://openalex.org/W2983179200","https://openalex.org/W2992768826","https://openalex.org/W3160506163","https://openalex.org/W2964317949","https://openalex.org/W3206059301","https://openalex.org/W3194276233","https://openalex.org/W2951081618","https://openalex.org/W2605417544","https://openalex.org/W3022049137","https://openalex.org/W2062518264"],"abstract_inverted_index":{"Feed-forward":[0],"networks":[1],"are":[2,29],"widely":[3],"used":[4,31],"in":[5],"cross-modal":[6,102],"applications":[7],"to":[8,18,22,32,52,66,94,117],"bridge":[9],"modalities":[10],"by":[11],"mapping":[12,51],"distributed":[13],"vectors":[14,28,64,143,151],"of":[15,41,49,61,68,109,124,140,148,154,177],"one":[16],"modality":[17],"the":[19,39,42,47,50,54,58,62,69,137,141,149,155,172,178],"other,":[20],"or":[21,36],"a":[23,85,106,121,159],"shared":[24],"space.":[25],"The":[26],"predicted":[27,63,142],"then":[30],"perform":[33],"e.g.,":[34],"retrieval":[35],"labeling.":[37],"Thus,":[38],"success":[40],"whole":[43],"system":[44],"relies":[45],"on":[46,97],"ability":[48],"make":[53],"neighborhood":[55,138,173],"structure":[56,139,176],"(i.e.,":[57,174],"pairwise":[59],"similarities)":[60],"akin":[65],"that":[67,147,153,165],"target":[70,156],"vectors.":[71,157,180],"However,":[72],"whether":[73],"this":[74,98],"is":[75],"achieved":[76],"has":[77],"not":[78,169],"been":[79],"investigated":[80],"yet.":[81],"Here,":[82],"we":[83,104,162],"propose":[84],"new":[86],"similarity":[87],"measure":[88],"and":[89,111,126,129],"two":[90],"ad":[91],"hoc":[92],"experiments":[93],"shed":[95],"light":[96],"issue.":[99],"In":[100,158],"three":[101],"benchmarks":[103],"learn":[105],"large":[107],"number":[108],"language-to-vision":[110],"vision-to-language":[112],"neural":[113],"network":[114],"mappings":[115],"(up":[116],"five":[118],"layers)":[119],"using":[120],"rich":[122],"diversity":[123],"image":[125],"text":[127],"features":[128],"loss":[130],"functions.":[131],"Our":[132],"results":[133],"reveal":[134],"that,":[135],"surprisingly,":[136],"consistently":[144],"resembles":[145],"more":[146],"input":[150,179],"than":[152],"second":[160],"experiment,":[161],"further":[163],"show":[164],"untrained":[166],"nets":[167],"do":[168],"significantly":[170],"disrupt":[171],"semantic)":[175]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}
