{"id":"https://openalex.org/W2898858752","doi":"https://doi.org/10.18653/v1/d18-1237","title":"MemoReader: Large-Scale Reading Comprehension through Neural Memory Controller","display_name":"MemoReader: Large-Scale Reading Comprehension through Neural Memory Controller","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2898858752","doi":"https://doi.org/10.18653/v1/d18-1237","mag":"2898858752"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d18-1237","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1237","pdf_url":"https://www.aclweb.org/anthology/D18-1237.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D18-1237.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109445323","display_name":"Seohyun Back","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]},{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seohyun Back","raw_affiliation_strings":["Korea University, Seoul, Korea","Samsung Research, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Samsung Research, Seoul, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036671957","display_name":"Seunghak Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seunghak Yu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052409554","display_name":"Sathish Reddy Indurthi","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sathish Reddy Indurthi","raw_affiliation_strings":["Samsung Research, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Samsung Research, Seoul, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080664764","display_name":"Jihie Kim","orcid":"https://orcid.org/0000-0003-2358-4021"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jihie Kim","raw_affiliation_strings":["Samsung Research, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Samsung Research, Seoul, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047912015","display_name":"Jaegul Choo","orcid":"https://orcid.org/0000-0003-1071-4835"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]},{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaegul Choo","raw_affiliation_strings":["Korea University, Seoul, Korea","Samsung Research, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Samsung Research, Seoul, Korea","institution_ids":["https://openalex.org/I2250650973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5080664764"],"corresponding_institution_ids":["https://openalex.org/I2250650973"],"apc_list":null,"apc_paid":null,"fwci":1.523,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.87376179,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2131","last_page":"2140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9975000023841858,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9883000254631042,"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":0.8607000112533569},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6319506168365479},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6019765734672546},{"id":"https://openalex.org/keywords/reading-comprehension","display_name":"Reading comprehension","score":0.5744180679321289},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.5687220096588135},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5371976494789124},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.47295138239860535},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.4693606495857239},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40340206027030945},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38355788588523865},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08898860216140747}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8607000112533569},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6319506168365479},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6019765734672546},{"id":"https://openalex.org/C2778780117","wikidata":"https://www.wikidata.org/wiki/Q3269423","display_name":"Reading comprehension","level":3,"score":0.5744180679321289},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.5687220096588135},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5371976494789124},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.47295138239860535},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.4693606495857239},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40340206027030945},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38355788588523865},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08898860216140747},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d18-1237","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1237","pdf_url":"https://www.aclweb.org/anthology/D18-1237.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d18-1237","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1237","pdf_url":"https://www.aclweb.org/anthology/D18-1237.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8799999952316284,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G3942910960","display_name":null,"funder_award_id":"(NRF) grant","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G6686156393","display_name":null,"funder_award_id":"Korean government (MSIP)","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322030","display_name":"Ministry of Science, ICT and Future Planning","ror":"https://ror.org/032e49973"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2898858752.pdf","grobid_xml":"https://content.openalex.org/works/W2898858752.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1525961042","https://openalex.org/W2143017621","https://openalex.org/W2157331557","https://openalex.org/W2250539671","https://openalex.org/W2530887700","https://openalex.org/W2551396370","https://openalex.org/W2552027021","https://openalex.org/W2563734883","https://openalex.org/W2626154462","https://openalex.org/W2734823783","https://openalex.org/W2739749670","https://openalex.org/W2740747242","https://openalex.org/W2752104716","https://openalex.org/W2765627424","https://openalex.org/W2766508367","https://openalex.org/W2770970123","https://openalex.org/W2798858969","https://openalex.org/W2887557046","https://openalex.org/W2950527759","https://openalex.org/W2951976932","https://openalex.org/W2953320089","https://openalex.org/W2962718483","https://openalex.org/W2962739339","https://openalex.org/W2962809918","https://openalex.org/W2962985038","https://openalex.org/W2963082277","https://openalex.org/W2963339397","https://openalex.org/W2963446712","https://openalex.org/W2963748441","https://openalex.org/W2963769536","https://openalex.org/W2963871484","https://openalex.org/W4294329082","https://openalex.org/W4295253143","https://openalex.org/W4299280717","https://openalex.org/W4303633609"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2082296339","https://openalex.org/W2161828220","https://openalex.org/W1972348076","https://openalex.org/W2083863157"],"abstract_inverted_index":{"Machine":[0],"reading":[1],"comprehension":[2],"helps":[3],"machines":[4],"learn":[5],"to":[6,26,37,42,58,104],"utilize":[7],"most":[8],"of":[9,17],"the":[10,15,96,127],"human":[11],"knowledge":[12],"written":[13],"in":[14,34,63,95],"form":[16],"text.":[18],"Existing":[19],"approaches":[20],"made":[21],"a":[22,38,52,60],"significant":[23],"progress":[24],"comparable":[25],"human-level":[27],"performance,":[28],"but":[29],"they":[30],"are":[31],"still":[32],"limited":[33],"understanding,":[35],"up":[36],"few":[39],"paragraphs,":[40],"failing":[41],"properly":[43],"comprehend":[44],"lengthy":[45,135],"document.":[46],"In":[47,66],"this":[48],"paper,":[49],"we":[50],"propose":[51],"novel":[53,72],"deep":[54],"neural":[55],"network":[56],"architecture":[57,78,100],"handle":[59],"long-range":[61],"dependency":[62],"RC":[64],"tasks.":[65],"detail,":[67],"our":[68],"method":[69,129],"has":[70],"two":[71],"aspects:":[73],"(1)":[74],"an":[75,81],"advanced":[76],"memory-augmented":[77],"and":[79,120],"(2)":[80],"expanded":[82],"gated":[83],"recurrent":[84],"unit":[85],"with":[86,112],"dense":[87],"connections":[88],"that":[89,126],"mitigate":[90],"potential":[91],"information":[92],"distortion":[93],"occurring":[94],"memory.":[97],"Our":[98],"proposed":[99,128],"is":[101],"widely":[102],"applicable":[103],"other":[105],"models.":[106],"We":[107],"have":[108],"performed":[109],"extensive":[110],"experiments":[111],"well-known":[113],"benchmark":[114],"datasets":[115],"such":[116],"as":[117],"TriviaQA,":[118],"QUASAR-T,":[119],"SQuAD.":[121],"The":[122],"experimental":[123],"results":[124],"demonstrate":[125],"outperforms":[130],"existing":[131],"methods,":[132],"especially":[133],"for":[134],"documents.":[136]},"counts_by_year":[{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
