{"id":"https://openalex.org/W2288995089","doi":"https://doi.org/10.18653/v1/p16-1086","title":"Text Understanding with the Attention Sum Reader Network","display_name":"Text Understanding with the Attention Sum Reader Network","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2288995089","doi":"https://doi.org/10.18653/v1/p16-1086","mag":"2288995089"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p16-1086","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1086","pdf_url":"https://www.aclweb.org/anthology/P16-1086.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 54th 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/P16-1086.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011017122","display_name":"Rudolf Kadlec","orcid":"https://orcid.org/0009-0009-6506-1721"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rudolf Kadlec","raw_affiliation_strings":["IBM Watson V Parku 4, Prague, Czech Republic","IBM (United States), Armonk, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Watson V Parku 4, Prague, Czech Republic","institution_ids":[]},{"raw_affiliation_string":"IBM (United States), Armonk, United States","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038602378","display_name":"Martin Schmid","orcid":"https://orcid.org/0000-0001-5341-9209"},"institutions":[{"id":"https://openalex.org/I21250087","display_name":"Charles University","ror":"https://ror.org/024d6js02","country_code":"CZ","type":"education","lineage":["https://openalex.org/I21250087"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Martin Schmid","raw_affiliation_strings":["IBM Watson V Parku 4, Prague, Czech Republic","Charles University, Prague, Czechia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Watson V Parku 4, Prague, Czech Republic","institution_ids":[]},{"raw_affiliation_string":"Charles University, Prague, Czechia","institution_ids":["https://openalex.org/I21250087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050872351","display_name":"Ond\u0159ej Bajgar","orcid":"https://orcid.org/0000-0002-6208-1534"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ond\u0159ej Bajgar","raw_affiliation_strings":["IBM Watson V Parku 4, Prague, Czech Republic","IBM (United States), Armonk, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Watson V Parku 4, Prague, Czech Republic","institution_ids":[]},{"raw_affiliation_string":"IBM (United States), Armonk, United States","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005624553","display_name":"Jan Kleindienst","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jan Kleindienst","raw_affiliation_strings":["IBM Watson V Parku 4, Prague, Czech Republic","IBM (United States), Armonk, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Watson V Parku 4, Prague, Czech Republic","institution_ids":[]},{"raw_affiliation_string":"IBM (United States), Armonk, United States","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011017122"],"corresponding_institution_ids":["https://openalex.org/I1341412227"],"apc_list":null,"apc_paid":null,"fwci":16.3471,"has_fulltext":true,"cited_by_count":46,"citation_normalized_percentile":{"value":0.99017943,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"908","last_page":"918"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":0.9977999925613403,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9965999722480774,"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/computer-science","display_name":"Computer science","score":0.7718908786773682},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6088899970054626},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5918176770210266},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5885875225067139},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.5677872896194458},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5573521852493286},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5490338206291199},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5305429100990295},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5016567707061768},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.4903142750263214},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.45276039838790894},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44861263036727905},{"id":"https://openalex.org/keywords/style","display_name":"Style (visual arts)","score":0.4298226833343506},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.37128978967666626},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.14882168173789978}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7718908786773682},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6088899970054626},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5918176770210266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5885875225067139},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.5677872896194458},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5573521852493286},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5490338206291199},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5305429100990295},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5016567707061768},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.4903142750263214},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.45276039838790894},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44861263036727905},{"id":"https://openalex.org/C2776445246","wikidata":"https://www.wikidata.org/wiki/Q1792644","display_name":"Style (visual arts)","level":2,"score":0.4298226833343506},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.37128978967666626},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.14882168173789978},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/p16-1086","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1086","pdf_url":"https://www.aclweb.org/anthology/P16-1086.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 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1603.01547","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1603.01547","pdf_url":"https://arxiv.org/pdf/1603.01547","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:2288995089","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1603.01547.pdf","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.1603.01547","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1603.01547","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/p16-1086","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1086","pdf_url":"https://www.aclweb.org/anthology/P16-1086.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 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2288995089.pdf","grobid_xml":"https://content.openalex.org/works/W2288995089.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W1924770834","https://openalex.org/W2113021982","https://openalex.org/W2125436846","https://openalex.org/W2126209950","https://openalex.org/W2171278097","https://openalex.org/W2250432970","https://openalex.org/W2270070752","https://openalex.org/W2411480514","https://openalex.org/W2475151947","https://openalex.org/W2507756961","https://openalex.org/W2949615363","https://openalex.org/W2963504252","https://openalex.org/W2964121744","https://openalex.org/W2964308564"],"related_works":["https://openalex.org/W2963595025","https://openalex.org/W2427527485","https://openalex.org/W2250539671","https://openalex.org/W2964308564","https://openalex.org/W2949615363","https://openalex.org/W2516930406","https://openalex.org/W2125436846","https://openalex.org/W1522301498","https://openalex.org/W2411480514","https://openalex.org/W2740747242","https://openalex.org/W2126209950","https://openalex.org/W2064675550","https://openalex.org/W2951815760","https://openalex.org/W2507756961","https://openalex.org/W2951008357","https://openalex.org/W2415755012","https://openalex.org/W3104486441","https://openalex.org/W2951534261","https://openalex.org/W2949776890","https://openalex.org/W1525961042"],"abstract_inverted_index":{"Several":[0],"large":[1],"cloze-style":[2],"context-questionanswer":[3],"datasets":[4],"have":[5],"been":[6],"introduced":[7],"recently:":[8],"the":[9,17,23,28,59,62,68,77,87,95,102,112],"CNN":[10],"and":[11,16],"Daily":[12],"Mail":[13],"news":[14],"data":[15],"Children's":[18],"Book":[19],"Test.":[20],"Thanks":[21],"to":[22,42,56,66],"size":[24],"of":[25,74,105,111],"these":[26],"datasets,":[27],"associated":[29],"text":[30],"comprehension":[31],"task":[32],"is":[33,80,97],"well":[34],"suited":[35],"for":[36,91],"deep-learning":[37],"techniques":[38],"that":[39,53],"currently":[40],"seem":[41],"outperform":[43],"all":[44,115],"alternative":[45],"approaches.":[46],"We":[47],"present":[48],"a":[49,71,98],"new,":[50],"simple":[51],"model":[52,88],"uses":[54],"attention":[55],"directly":[57],"pick":[58],"answer":[60,69,96],"from":[61,101],"context":[63],"as":[64,79],"opposed":[65],"computing":[67],"using":[70],"blended":[72],"representation":[73],"words":[75],"in":[76,82],"document":[78],"usual":[81],"similar":[83],"models.":[84],"This":[85],"makes":[86],"particularly":[89],"suitable":[90],"questionanswering":[92],"problems":[93],"where":[94],"single":[99],"word":[100],"document.":[103],"Ensemble":[104],"our":[106],"models":[107],"sets":[108],"new":[109],"state":[110],"art":[113],"on":[114],"evaluated":[116],"datasets.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":16},{"year":2016,"cited_by_count":6}],"updated_date":"2026-05-13T06:04:23.736269","created_date":"2025-10-10T00:00:00"}
