{"id":"https://openalex.org/W3162371491","doi":"https://doi.org/10.1109/smc52423.2021.9659223","title":"Show Why the Answer is Correct! Towards Explainable AI using Compositional Temporal Attention","display_name":"Show Why the Answer is Correct! Towards Explainable AI using Compositional Temporal Attention","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W3162371491","doi":"https://doi.org/10.1109/smc52423.2021.9659223","mag":"3162371491"},"language":"en","primary_location":{"id":"doi:10.1109/smc52423.2021.9659223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc52423.2021.9659223","pdf_url":null,"source":{"id":"https://openalex.org/S4363607761","display_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5081670281","display_name":"Nihar Bendre","orcid":"https://orcid.org/0000-0003-3480-4616"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nihar Bendre","raw_affiliation_strings":["AILA (Artificial Intelligent Laboratory and Autonomy), University of Texas at San Antonio, San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"AILA (Artificial Intelligent Laboratory and Autonomy), University of Texas at San Antonio, San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076318084","display_name":"Kevin Desai","orcid":"https://orcid.org/0000-0002-2964-8981"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin Desai","raw_affiliation_strings":["AILA (Artificial Intelligent Laboratory and Autonomy), University of Texas at San Antonio, San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"AILA (Artificial Intelligent Laboratory and Autonomy), University of Texas at San Antonio, San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017210698","display_name":"Peyman Najafirad","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peyman Najafirad","raw_affiliation_strings":["AILA (Artificial Intelligent Laboratory and Autonomy), University of Texas at San Antonio, San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"AILA (Artificial Intelligent Laboratory and Autonomy), University of Texas at San Antonio, San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081670281"],"corresponding_institution_ids":["https://openalex.org/I45438204"],"apc_list":null,"apc_paid":null,"fwci":0.2614,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.62514401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3006","last_page":"3012"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9937999844551086,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9829999804496765,"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/principle-of-compositionality","display_name":"Principle of compositionality","score":0.9506263732910156},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8369994759559631},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7843711376190186},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.7718238830566406},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6790057420730591},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6456035375595093},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.5447708964347839},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5318318009376526},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.48137977719306946},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47343066334724426},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3421526253223419},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.08204802870750427}],"concepts":[{"id":"https://openalex.org/C121375916","wikidata":"https://www.wikidata.org/wiki/Q936559","display_name":"Principle of compositionality","level":2,"score":0.9506263732910156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8369994759559631},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7843711376190186},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.7718238830566406},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6790057420730591},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6456035375595093},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.5447708964347839},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5318318009376526},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.48137977719306946},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47343066334724426},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3421526253223419},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.08204802870750427},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc52423.2021.9659223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc52423.2021.9659223","pdf_url":null,"source":{"id":"https://openalex.org/S4363607761","display_name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W627986001","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1933349210","https://openalex.org/W2082435639","https://openalex.org/W2133564696","https://openalex.org/W2190656909","https://openalex.org/W2194775991","https://openalex.org/W2412400526","https://openalex.org/W2471094925","https://openalex.org/W2558535589","https://openalex.org/W2560730294","https://openalex.org/W2561715562","https://openalex.org/W2597425697","https://openalex.org/W2608030593","https://openalex.org/W2626778328","https://openalex.org/W2734708268","https://openalex.org/W2950761309","https://openalex.org/W2951619830","https://openalex.org/W2963143606","https://openalex.org/W2963224792","https://openalex.org/W2963383024","https://openalex.org/W2963954913","https://openalex.org/W2964118342","https://openalex.org/W2964308564","https://openalex.org/W2964345214","https://openalex.org/W2976260559","https://openalex.org/W2997591391","https://openalex.org/W3001893196","https://openalex.org/W3010535384","https://openalex.org/W3011681065","https://openalex.org/W3012111773","https://openalex.org/W3035517717","https://openalex.org/W3036453007","https://openalex.org/W3046014872","https://openalex.org/W3098351727","https://openalex.org/W3108512475","https://openalex.org/W3110388292","https://openalex.org/W3151972839","https://openalex.org/W3194342258","https://openalex.org/W4250583963","https://openalex.org/W4297785524","https://openalex.org/W4298392976","https://openalex.org/W4385245566","https://openalex.org/W6620100662","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6679434410","https://openalex.org/W6682086655","https://openalex.org/W6687239747","https://openalex.org/W6736769356","https://openalex.org/W6739901393","https://openalex.org/W6741207388","https://openalex.org/W6779540071","https://openalex.org/W6781819027","https://openalex.org/W6793307265"],"related_works":["https://openalex.org/W4251923961","https://openalex.org/W1526190050","https://openalex.org/W2477397717","https://openalex.org/W17155033","https://openalex.org/W2500457737","https://openalex.org/W4287025733","https://openalex.org/W4317425742","https://openalex.org/W2010490241","https://openalex.org/W3192500523","https://openalex.org/W4385437088"],"abstract_inverted_index":{"Visual":[0,165],"Question":[1,166],"Answering":[2,167],"(VQA)":[3],"models":[4,22,68],"have":[5],"achieved":[6],"significant":[7],"success":[8,14],"in":[9,36,126],"recent":[10],"times.":[11],"Despite":[12],"the":[13,27,47,63,140,149,161],"of":[15,46,66,103,130],"VQA":[16],"models,":[17],"they":[18],"are":[19,56],"mostly":[20],"black-box":[21,64],"providing":[23],"no":[24],"reasoning":[25,136],"about":[26],"predicted":[28],"answer,":[29],"thus":[30,55,175],"raising":[31],"questions":[32,53,132],"for":[33,164,179],"their":[34],"applicability":[35],"safety-critical":[37],"such":[38],"as":[39,137,169,171],"autonomous":[40],"systems":[41],"and":[42,54,69,90,133,154,185],"cyber-security.":[43],"Current":[44],"state":[45],"art":[48],"fail":[49],"to":[50,58,71,105,114,120,138],"better":[51,74,128,173],"complex":[52,131],"unable":[57],"exploit":[59,75],"compositionality.":[60],"To":[61],"minimize":[62],"effect":[65],"these":[67,115],"also":[70,134],"make":[72],"them":[73],"compositionality,":[76],"we":[77],"propose":[78],"a":[79,87,101,107,143],"Dynamic":[80],"Neural":[81],"Network":[82],"(DMN),":[83],"which":[84],"can":[85],"understand":[86],"particular":[88,144],"question":[89],"then":[91],"dynamically":[92],"assemble":[93],"various":[94],"relatively":[95],"shallow":[96],"deep":[97,116],"learning":[98,117],"modules":[99,104,119],"from":[100],"pool":[102],"form":[106],"network.":[108],"We":[109],"incorporate":[110],"compositional":[111],"temporal":[112],"attention":[113],"based":[118],"increase":[121],"compositionality":[122],"exploitation.":[123],"This":[124],"results":[125],"achieving":[127],"understanding":[129],"provides":[135,172],"why":[139],"module":[141],"predicts":[142],"answer.":[145],"Experimental":[146],"analysis":[147],"on":[148],"two":[150],"benchmark":[151],"datasets,":[152],"VQA2.0":[153],"CLEVR,":[155],"depicts":[156],"that":[157],"our":[158],"model":[159],"outperforms":[160],"previous":[162],"approaches":[163],"task":[168],"well":[170],"reasoning,":[174],"making":[176],"it":[177],"reliable":[178],"mission":[180],"critical":[181],"applications":[182],"like":[183],"safety":[184],"security.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}