{"id":"https://openalex.org/W3182333745","doi":"https://doi.org/10.1109/lra.2021.3108500","title":"Target-Dependent UNITER: A Transformer-Based Multimodal Language Comprehension Model for Domestic Service Robots","display_name":"Target-Dependent UNITER: A Transformer-Based Multimodal Language Comprehension Model for Domestic Service Robots","publication_year":2021,"publication_date":"2021-08-30","ids":{"openalex":"https://openalex.org/W3182333745","doi":"https://doi.org/10.1109/lra.2021.3108500","mag":"3182333745"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2021.3108500","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2021.3108500","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2107.00811","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042770831","display_name":"Shintaro Ishikawa","orcid":"https://orcid.org/0000-0003-0810-3613"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shintaro Ishikawa","raw_affiliation_strings":["Keio University, Kanagawa, Japan","KEIO UNIVERSITY"],"raw_orcid":"https://orcid.org/0000-0003-0810-3613","affiliations":[{"raw_affiliation_string":"Keio University, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"KEIO UNIVERSITY","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033744547","display_name":"Komei Sugiura","orcid":"https://orcid.org/0000-0002-0261-0510"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Komei Sugiura","raw_affiliation_strings":["Keio University, Kanagawa, Japan","KEIO UNIVERSITY"],"raw_orcid":"https://orcid.org/0000-0002-0261-0510","affiliations":[{"raw_affiliation_string":"Keio University, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"KEIO UNIVERSITY","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5042770831"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.07898011,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"6","issue":"4","first_page":"8401","last_page":"8408"},"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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9991999864578247,"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":0.7966264486312866},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7686819434165955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6050871014595032},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6029139757156372},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.47191813588142395},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.46873101592063904},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4520230293273926},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4288231134414673},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4139467477798462},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0750785768032074},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07254070043563843}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7966264486312866},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7686819434165955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6050871014595032},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6029139757156372},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.47191813588142395},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.46873101592063904},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4520230293273926},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4288231134414673},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4139467477798462},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0750785768032074},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07254070043563843},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/lra.2021.3108500","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2021.3108500","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2107.00811","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.00811","pdf_url":"https://arxiv.org/pdf/2107.00811","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":null,"raw_type":"text"},{"id":"mag:3182333745","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2107.00811","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.2107.00811","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2107.00811","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":"pmh:oai:arXiv.org:2107.00811","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.00811","pdf_url":"https://arxiv.org/pdf/2107.00811","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321680","display_name":"New Energy and Industrial Technology Development Organization","ror":"https://ror.org/0055k7a87"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3182333745.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1543294385","https://openalex.org/W1686810756","https://openalex.org/W1840435438","https://openalex.org/W1897507002","https://openalex.org/W1933349210","https://openalex.org/W2011442902","https://openalex.org/W2064675550","https://openalex.org/W2070935310","https://openalex.org/W2125447031","https://openalex.org/W2151498684","https://openalex.org/W2194775991","https://openalex.org/W2251512949","https://openalex.org/W2558809543","https://openalex.org/W2583360688","https://openalex.org/W2613718673","https://openalex.org/W2890725233","https://openalex.org/W2907143950","https://openalex.org/W2912371042","https://openalex.org/W2950761309","https://openalex.org/W2953084091","https://openalex.org/W2953626316","https://openalex.org/W2960655175","https://openalex.org/W2962716343","https://openalex.org/W2963177331","https://openalex.org/W2963403868","https://openalex.org/W2963644680","https://openalex.org/W2963811535","https://openalex.org/W2970608575","https://openalex.org/W2972544311","https://openalex.org/W2998552463","https://openalex.org/W3034201026","https://openalex.org/W3034266838","https://openalex.org/W3044312764","https://openalex.org/W3090449556","https://openalex.org/W6637373629","https://openalex.org/W6682086655","https://openalex.org/W6691589334","https://openalex.org/W6719667659","https://openalex.org/W6727690538","https://openalex.org/W6739901393","https://openalex.org/W6753277404","https://openalex.org/W6758704467","https://openalex.org/W6766071559","https://openalex.org/W6766904570","https://openalex.org/W6791353385"],"related_works":["https://openalex.org/W3196798710","https://openalex.org/W3178489527","https://openalex.org/W2767521608","https://openalex.org/W2925229769","https://openalex.org/W2066990677","https://openalex.org/W858561504","https://openalex.org/W3098970982","https://openalex.org/W2267737560","https://openalex.org/W2901904725","https://openalex.org/W2552381313","https://openalex.org/W3000903387","https://openalex.org/W2799122342","https://openalex.org/W2225735676","https://openalex.org/W2994983839","https://openalex.org/W2964131627","https://openalex.org/W2581528920","https://openalex.org/W2182177114","https://openalex.org/W2520761760","https://openalex.org/W3080223684","https://openalex.org/W3080857812"],"abstract_inverted_index":{"Currently,":[0],"domestic":[1],"service":[2],"robots":[3],"have":[4],"an":[5,65,75],"insufficient":[6],"ability":[7],"to":[8],"interact":[9],"naturally":[10],"through":[11],"language.":[12],"This":[13],"is":[14,19,74,105],"because":[15],"understanding":[16],"human":[17],"instructions":[18],"complicated":[20],"by":[21,58,94],"various":[22],"ambiguities.":[23],"In":[24,39],"existing":[25],"methods,":[26],"the":[27,32,48,51,61,69,78,91,112,119],"referring":[28],"expressions":[29],"that":[30,82,115],"specify":[31],"relationships":[33],"between":[34,50],"objects":[35,56],"were":[36],"insufficiently":[37],"modeled.":[38],"this":[40],"letter,":[41],"we":[42],"propose":[43],"Target-dependent":[44,116],"UNITER,":[45],"which":[46],"learns":[47],"relationship":[49],"target":[52],"object":[53],"and":[54,111],"other":[55],"directly":[57],"focusing":[59],"on":[60,86,107],"relevant":[62],"regions":[63],"within":[64],"image,":[66],"rather":[67],"than":[68],"whole":[70],"image.":[71],"Our":[72,103],"method":[73,121],"extension":[76],"of":[77,124],"UNITER":[79,92,117],"[1]-based":[80],"Transformer":[81],"can":[83],"be":[84],"pretrained":[85],"general-purpose":[87],"datasets.":[88],"We":[89],"extend":[90],"approach":[93],"introducing":[95],"a":[96],"new":[97],"architecture":[98],"for":[99],"handling":[100],"candidate":[101],"objects.":[102],"model":[104],"validated":[106],"two":[108],"standard":[109],"datasets,":[110],"results":[113],"show":[114],"outperforms":[118],"baseline":[120],"in":[122],"terms":[123],"classification":[125],"accuracy.":[126]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-07-25T00:00:00"}
