{"id":"https://openalex.org/W2949153209","doi":"https://doi.org/10.18653/v1/p19-1434","title":"Episodic Memory Reader: Learning What to Remember for Question Answering from Streaming Data","display_name":"Episodic Memory Reader: Learning What to Remember for Question Answering from Streaming Data","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2949153209","doi":"https://doi.org/10.18653/v1/p19-1434","mag":"2949153209"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1434","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1434","pdf_url":"https://www.aclweb.org/anthology/P19-1434.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1434.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002065506","display_name":"Moonsu Han","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Moonsu Han","raw_affiliation_strings":["AITRICS 2 , Seoul, South Korea","KAIST 1 , Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AITRICS 2 , Seoul, South Korea","institution_ids":[]},{"raw_affiliation_string":"KAIST 1 , Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110617736","display_name":"Minki Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minki Kang","raw_affiliation_strings":["AITRICS 2 , Seoul, South Korea","KAIST 1 , Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AITRICS 2 , Seoul, South Korea","institution_ids":[]},{"raw_affiliation_string":"KAIST 1 , Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103934403","display_name":"Hyun-Woo Jung","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunwoo Jung","raw_affiliation_strings":["AITRICS 2 , Seoul, South Korea","KAIST 1 , Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AITRICS 2 , Seoul, South Korea","institution_ids":[]},{"raw_affiliation_string":"KAIST 1 , Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070302452","display_name":"Sung Ju Hwang","orcid":"https://orcid.org/0000-0002-9675-2324"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sung Ju Hwang","raw_affiliation_strings":["AITRICS 2 , Seoul, South Korea","KAIST 1 , Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AITRICS 2 , Seoul, South Korea","institution_ids":[]},{"raw_affiliation_string":"KAIST 1 , Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.549,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.73761823,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4407","last_page":"4417"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.998199999332428,"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":0.8831859827041626},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7981350421905518},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6572622060775757},{"id":"https://openalex.org/keywords/episodic-memory","display_name":"Episodic memory","score":0.6152438521385193},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5358354449272156},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5133673548698425},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4934336245059967},{"id":"https://openalex.org/keywords/auxiliary-memory","display_name":"Auxiliary memory","score":0.47007232904434204},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4265805184841156},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41800954937934875},{"id":"https://openalex.org/keywords/streaming-data","display_name":"Streaming data","score":0.4172821640968323},{"id":"https://openalex.org/keywords/context-dependent-memory","display_name":"Context-dependent memory","score":0.41220107674598694},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34395328164100647},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.25197094678878784},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.1753588616847992},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13302484154701233},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.0926135778427124}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8831859827041626},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7981350421905518},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6572622060775757},{"id":"https://openalex.org/C88576662","wikidata":"https://www.wikidata.org/wiki/Q18646","display_name":"Episodic memory","level":3,"score":0.6152438521385193},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5358354449272156},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5133673548698425},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4934336245059967},{"id":"https://openalex.org/C82687282","wikidata":"https://www.wikidata.org/wiki/Q66221","display_name":"Auxiliary memory","level":2,"score":0.47007232904434204},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4265805184841156},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41800954937934875},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.4172821640968323},{"id":"https://openalex.org/C76679254","wikidata":"https://www.wikidata.org/wiki/Q5165163","display_name":"Context-dependent memory","level":4,"score":0.41220107674598694},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34395328164100647},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.25197094678878784},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1753588616847992},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13302484154701233},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.0926135778427124},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","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/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C36668950","wikidata":"https://www.wikidata.org/wiki/Q5500279","display_name":"Free recall","level":3,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1434","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1434","pdf_url":"https://www.aclweb.org/anthology/P19-1434.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1434","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1434","pdf_url":"https://www.aclweb.org/anthology/P19-1434.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8600000143051147,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1343409141","display_name":null,"funder_award_id":"2016-0-00563","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2949153209.pdf","grobid_xml":"https://content.openalex.org/works/W2949153209.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1525961042","https://openalex.org/W1544827683","https://openalex.org/W1793121960","https://openalex.org/W2125436846","https://openalex.org/W2131494463","https://openalex.org/W2250539671","https://openalex.org/W2293453011","https://openalex.org/W2470713034","https://openalex.org/W2530887700","https://openalex.org/W2551396370","https://openalex.org/W2739749670","https://openalex.org/W2741263286","https://openalex.org/W2753798143","https://openalex.org/W2788448041","https://openalex.org/W2890498499","https://openalex.org/W2890904455","https://openalex.org/W2896457183","https://openalex.org/W2898858752","https://openalex.org/W2949615363","https://openalex.org/W2950527759","https://openalex.org/W2951008357","https://openalex.org/W2962718483","https://openalex.org/W2962790689","https://openalex.org/W2962808855","https://openalex.org/W2962910007","https://openalex.org/W2962938145","https://openalex.org/W2962985038","https://openalex.org/W2963159735","https://openalex.org/W2963339397","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963541336","https://openalex.org/W2963564796","https://openalex.org/W2963579811","https://openalex.org/W2963748441","https://openalex.org/W2963781647","https://openalex.org/W2963890755","https://openalex.org/W2964043796","https://openalex.org/W2964091467","https://openalex.org/W2964121744","https://openalex.org/W3104486441","https://openalex.org/W4230563027","https://openalex.org/W4295122349","https://openalex.org/W4295253143","https://openalex.org/W4303633609","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W344766441","https://openalex.org/W2069432434","https://openalex.org/W3105069238","https://openalex.org/W4366494932","https://openalex.org/W2086916720","https://openalex.org/W2040721328","https://openalex.org/W4211068090","https://openalex.org/W1976526055","https://openalex.org/W1764825819","https://openalex.org/W2495955961"],"abstract_inverted_index":{"We":[0,141],"consider":[1],"a":[2,51,98,114,146],"novel":[3,52],"question":[4],"answering":[5,87],"(QA)":[6],"task":[7],"where":[8],"the":[9,25,72,102,119,124,127,138,183],"machine":[10],"needs":[11],"to":[12,33,40,63,96,108,130],"read":[13],"from":[14],"large":[15],"streaming":[16],"data":[17],"(long":[18],"documents":[19],"or":[20,126,175],"videos)":[21],"without":[22],"knowing":[23],"when":[24,101],"questions":[26],"will":[27],"be":[28],"given,":[29],"which":[30,60,164],"is":[31,104],"difficult":[32],"solve":[34],"with":[35],"existing":[36],"QA":[37,111,156,160],"methods":[38],"due":[39],"their":[41],"lack":[42],"of":[43,186],"scalability.":[44],"To":[45],"tackle":[46],"this":[47],"problem,":[48],"we":[49,61,91],"propose":[50],"end-to-end":[53],"deep":[54],"network":[55],"model":[56,144],"for":[57,86],"reading":[58],"comprehension,":[59],"refer":[62],"as":[64,150,152],"Episodic":[65],"Memory":[66],"Reader":[67],"(EMR)":[68],"that":[69,82,133,180],"sequentially":[70],"reads":[71],"input":[73],"contexts":[74],"into":[75],"an":[76,93,176],"external":[77,120],"memory,":[78],"while":[79,117],"replacing":[80],"memories":[81],"are":[83],"less":[84],"important":[85],"unseen":[88],"questions.":[89],"Specifically,":[90],"train":[92],"RL":[94,177],"agent":[95],"replace":[97],"memory":[99,103,121,139,172],"entry":[100],"full,":[105],"in":[106],"order":[107],"maximize":[109],"its":[110],"accuracy":[112],"at":[113],"future":[115],"timepoint,":[116],"encoding":[118],"using":[122],"either":[123],"GRU":[125],"Transformer":[128],"architecture":[129],"learn":[131],"representations":[132],"considers":[134],"relative":[135],"importance":[136,185],"between":[137],"entries.":[140],"validate":[142],"our":[143],"on":[145,163],"synthetic":[147],"dataset":[148],"(bAbI)":[149],"well":[151],"real-world":[153],"large-scale":[154],"textual":[155],"(TriviaQA)":[157],"and":[158],"video":[159],"(TVQA)":[161],"datasets,":[162],"it":[165],"achieves":[166],"significant":[167],"improvements":[168],"over":[169],"rule":[170],"based":[171,178],"scheduling":[173],"policies":[174],"baseline":[179],"independently":[181],"learns":[182],"query-specific":[184],"each":[187],"memory.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
