{"id":"https://openalex.org/W2798312813","doi":"https://doi.org/10.18653/v1/p18-1176","title":"Did the Model Understand the Question?","display_name":"Did the Model Understand the Question?","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2798312813","doi":"https://doi.org/10.18653/v1/p18-1176","mag":"2798312813"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p18-1176","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1176","pdf_url":"https://www.aclweb.org/anthology/P18-1176.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 1: Long 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/P18-1176.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019814805","display_name":"Pramod Kaushik Mudrakarta","orcid":null},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pramod Kaushik Mudrakarta","raw_affiliation_strings":["University of Chicago, Chicago, United States"],"affiliations":[{"raw_affiliation_string":"University of Chicago, Chicago, United States","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069391199","display_name":"Ankur Taly","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ankur Taly","raw_affiliation_strings":["Google (United States), Mountain View, United States"],"affiliations":[{"raw_affiliation_string":"Google (United States), Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008661612","display_name":"Mukund Sundararajan","orcid":"https://orcid.org/0000-0002-2031-7545"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mukund Sundararajan","raw_affiliation_strings":["Google (United States), Mountain View, United States"],"affiliations":[{"raw_affiliation_string":"Google (United States), Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024390954","display_name":"Kedar Dhamdhere","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kedar Dhamdhere","raw_affiliation_strings":["Google (United States), Mountain View, United States"],"affiliations":[{"raw_affiliation_string":"Google (United States), Mountain View, United States","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5019814805"],"corresponding_institution_ids":["https://openalex.org/I40347166"],"apc_list":null,"apc_paid":null,"fwci":3.03203333,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.91134247,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1896","last_page":"1906"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9986000061035156,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9980999827384949,"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/question-answering","display_name":"Question answering","score":0.7886636257171631},{"id":"https://openalex.org/keywords/paragraph","display_name":"Paragraph","score":0.6988061666488647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6951517462730408},{"id":"https://openalex.org/keywords/attribution","display_name":"Attribution","score":0.6731452941894531},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5972009897232056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5652804374694824},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5430594682693481},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5136991739273071},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.505556583404541},{"id":"https://openalex.org/keywords/reading-comprehension","display_name":"Reading comprehension","score":0.4172828495502472},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.28779226541519165},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.24178245663642883},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.20763978362083435},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.1797025501728058},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.10440558195114136}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7886636257171631},{"id":"https://openalex.org/C2777206241","wikidata":"https://www.wikidata.org/wiki/Q194431","display_name":"Paragraph","level":2,"score":0.6988061666488647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6951517462730408},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.6731452941894531},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5972009897232056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5652804374694824},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5430594682693481},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5136991739273071},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.505556583404541},{"id":"https://openalex.org/C2778780117","wikidata":"https://www.wikidata.org/wiki/Q3269423","display_name":"Reading comprehension","level":3,"score":0.4172828495502472},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.28779226541519165},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.24178245663642883},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.20763978362083435},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.1797025501728058},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.10440558195114136},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/p18-1176","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1176","pdf_url":"https://www.aclweb.org/anthology/P18-1176.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 1: Long Papers)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1805.05492","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1805.05492","pdf_url":"https://arxiv.org/pdf/1805.05492","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:2798312813","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1805.05492v1","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.1805.05492","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1805.05492","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/p18-1176","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1176","pdf_url":"https://www.aclweb.org/anthology/P18-1176.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 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.550000011920929,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2798312813.pdf","grobid_xml":"https://content.openalex.org/works/W2798312813.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W2101964891","https://openalex.org/W2123045220","https://openalex.org/W2250539671","https://openalex.org/W2282821441","https://openalex.org/W2346578521","https://openalex.org/W2412400526","https://openalex.org/W2427527485","https://openalex.org/W2463267937","https://openalex.org/W2465944011","https://openalex.org/W2557046785","https://openalex.org/W2608030593","https://openalex.org/W2616125804","https://openalex.org/W2738015883","https://openalex.org/W2757361303","https://openalex.org/W2792534906","https://openalex.org/W2949197630","https://openalex.org/W2949800357","https://openalex.org/W2950394196","https://openalex.org/W2950761309","https://openalex.org/W2952211726","https://openalex.org/W2962749469","https://openalex.org/W2962851944","https://openalex.org/W2963207607","https://openalex.org/W2963890019","https://openalex.org/W2964345214","https://openalex.org/W3101609372"],"related_works":["https://openalex.org/W2963615251","https://openalex.org/W2964308564","https://openalex.org/W2896457183","https://openalex.org/W2250539671","https://openalex.org/W2963969878","https://openalex.org/W3105630949","https://openalex.org/W3186135811","https://openalex.org/W2903320418","https://openalex.org/W3184942323","https://openalex.org/W2473519260","https://openalex.org/W2052713744","https://openalex.org/W2104616787","https://openalex.org/W3173356693","https://openalex.org/W2181891502","https://openalex.org/W2588425885","https://openalex.org/W3100378811","https://openalex.org/W3206562650","https://openalex.org/W3037843601","https://openalex.org/W2976505836","https://openalex.org/W3031001133"],"abstract_inverted_index":{"We":[0],"analyze":[1],"state-of-the-art":[2],"deep":[3,32],"learning":[4],"models":[5],"for":[6,121],"three":[7],"tasks:":[8],"question":[9,37,61,73],"answering":[10,62,74],"on":[11,94],"(1)":[12],"images,":[13],"(2)":[14],"tables,":[15],"and":[16,68,91,109],"(3)":[17],"passages":[18],"of":[19,24,49,58,70,107,112],"text.":[20],"Using":[21],"the":[22,56,122,131,137],"notion":[23],"\\emph{attribution}":[25],"(word":[26],"importance),":[27],"we":[28,42,81],"find":[29],"that":[30,69,101,133],"these":[31],"networks":[33],"often":[34],"ignore":[35],"important":[36],"terms.":[38],"Leveraging":[39],"such":[40],"behavior,":[41],"perturb":[43],"questions":[44],"to":[45,66,78],"craft":[46],"a":[47,59,71,116],"variety":[48],"adversarial":[50],"examples.":[51],"Our":[52,98],"strongest":[53],"attacks":[54,87],"drop":[55],"accuracy":[57,108],"visual":[60],"model":[63,75,113,117,132],"from":[64,76],"$61.1\\%$":[65],"$19\\%$,":[67],"tabular":[72],"$33.5\\%$":[77],"$3.3\\%$.":[79],"Additionally,":[80],"show":[82],"how":[83],"attributions":[84,102,125],"can":[85,103,126],"strengthen":[86],"proposed":[88],"by":[89],"Jia":[90],"Liang":[92],"(2017)":[93],"paragraph":[95],"comprehension":[96],"models.":[97],"results":[99],"demonstrate":[100],"augment":[104],"standard":[105],"measures":[106],"empower":[110],"investigation":[111],"performance.":[114],"When":[115],"is":[118],"accurate":[119],"but":[120],"wrong":[123],"reasons,":[124],"surface":[127],"erroneous":[128],"logic":[129],"in":[130,136],"indicates":[134],"inadequacies":[135],"test":[138],"data.":[139]},"counts_by_year":[{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}