{"id":"https://openalex.org/W2611955023","doi":"https://doi.org/10.18653/v1/d17-1097","title":"The Promise of Premise: Harnessing Question Premises in Visual Question Answering","display_name":"The Promise of Premise: Harnessing Question Premises in Visual Question Answering","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2611955023","doi":"https://doi.org/10.18653/v1/d17-1097","mag":"2611955023"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d17-1097","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1097","pdf_url":"https://www.aclweb.org/anthology/D17-1097.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D17-1097.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074296380","display_name":"Aroma Mahendru","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aroma Mahendru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110751285","display_name":"Viraj Prabhu","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Viraj Prabhu","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, United States","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082487441","display_name":"Akrit Mohapatra","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Akrit Mohapatra","raw_affiliation_strings":["Virginia Tech, Blacksburg, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, United States","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014035752","display_name":"Dhruv Batra","orcid":"https://orcid.org/0000-0002-1358-0011"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dhruv Batra","raw_affiliation_strings":["Georgia Institute of Technology","Georgia Institute of Technology, Atlanta, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, United States","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051259505","display_name":"Stefan Lee","orcid":"https://orcid.org/0000-0001-5953-1963"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stefan Lee","raw_affiliation_strings":["Virginia Tech, Blacksburg, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, United States","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"926","last_page":"935"},"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":0.995199978351593,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9851999878883362,"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/question-answering","display_name":"Question answering","score":0.8019256591796875},{"id":"https://openalex.org/keywords/premise","display_name":"Premise","score":0.7798395156860352},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7326121926307678},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.659083366394043},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6328088045120239},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6277598142623901},{"id":"https://openalex.org/keywords/premises","display_name":"Premises","score":0.5668365955352783},{"id":"https://openalex.org/keywords/forcing","display_name":"Forcing (mathematics)","score":0.47238636016845703},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4444003999233246},{"id":"https://openalex.org/keywords/questions-and-answers","display_name":"Questions and answers","score":0.4279562532901764},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.29262056946754456},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.19255194067955017},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0834081768989563}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.8019256591796875},{"id":"https://openalex.org/C2778023277","wikidata":"https://www.wikidata.org/wiki/Q321703","display_name":"Premise","level":2,"score":0.7798395156860352},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7326121926307678},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.659083366394043},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6328088045120239},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6277598142623901},{"id":"https://openalex.org/C2780613260","wikidata":"https://www.wikidata.org/wiki/Q670151","display_name":"Premises","level":2,"score":0.5668365955352783},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.47238636016845703},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4444003999233246},{"id":"https://openalex.org/C3019144022","wikidata":"https://www.wikidata.org/wiki/Q4124998","display_name":"Questions and answers","level":2,"score":0.4279562532901764},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.29262056946754456},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.19255194067955017},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0834081768989563},{"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},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/d17-1097","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1097","pdf_url":"https://www.aclweb.org/anthology/D17-1097.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1705.00601","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1705.00601","pdf_url":"https://arxiv.org/pdf/1705.00601","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:2611955023","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1705.00601","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.1705.00601","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1705.00601","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":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/v1/d17-1097","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1097","pdf_url":"https://www.aclweb.org/anthology/D17-1097.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2611955023.pdf","grobid_xml":"https://content.openalex.org/works/W2611955023.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2962685807","https://openalex.org/W2949690500","https://openalex.org/W2951435327","https://openalex.org/W2466071179","https://openalex.org/W2786900223","https://openalex.org/W3207316473","https://openalex.org/W2810059778","https://openalex.org/W3141357389","https://openalex.org/W2798877128","https://openalex.org/W2950541914","https://openalex.org/W3201174429","https://openalex.org/W3174776104","https://openalex.org/W2952061055","https://openalex.org/W2942659397","https://openalex.org/W3161066177","https://openalex.org/W3153457449","https://openalex.org/W3204848761","https://openalex.org/W1999343847","https://openalex.org/W2165925469","https://openalex.org/W3186431300"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"make":[4],"a":[5],"simple":[6],"observation":[7],"that":[8,23],"questions":[9],"about":[10,25],"images":[11],"often":[12],"contain":[13],"premises":[14,26],"-objects":[15],"and":[16],"relationships":[17],"implied":[18],"by":[19],"the":[20],"question":[21],"-and":[22],"reasoning":[24],"can":[27],"help":[28],"Visual":[29],"Question":[30],"Answering":[31],"(VQA)":[32],"models":[33],"respond":[34],"more":[35],"intelligently":[36],"to":[37],"irrelevant":[38],"or":[39],"previously":[40],"unseen":[41],"questions.":[42]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
