{"id":"https://openalex.org/W2963964519","doi":"https://doi.org/10.18653/v1/w16-1608","title":"Towards Abstraction from Extraction: Multiple Timescale Gated Recurrent Unit for Summarization","display_name":"Towards Abstraction from Extraction: Multiple Timescale Gated Recurrent Unit for Summarization","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2963964519","doi":"https://doi.org/10.18653/v1/w16-1608","mag":"2963964519"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w16-1608","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-1608","pdf_url":"https://www.aclweb.org/anthology/W16-1608.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 1st Workshop on Representation Learning for NLP","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W16-1608.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100362650","display_name":"Minsoo Kim","orcid":"https://orcid.org/0000-0001-7056-1952"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Minsoo Kim","raw_affiliation_strings":["School of Electronics Engineering Kyungpook National University Daegu, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering Kyungpook National University Daegu, South Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069774616","display_name":"Dennis Singh Moirangthem","orcid":"https://orcid.org/0000-0001-5200-1601"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dennis Singh Moirangthem","raw_affiliation_strings":["School of Electronics Engineering Kyungpook National University Daegu, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering Kyungpook National University Daegu, South Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100342785","display_name":"Minho Lee","orcid":"https://orcid.org/0000-0003-4549-8933"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minho Lee","raw_affiliation_strings":["School of Electronics Engineering Kyungpook National University Daegu, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering Kyungpook National University Daegu, South Korea","institution_ids":["https://openalex.org/I31419693"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100362650"],"corresponding_institution_ids":["https://openalex.org/I31419693"],"apc_list":null,"apc_paid":null,"fwci":5.7646,"has_fulltext":true,"cited_by_count":31,"citation_normalized_percentile":{"value":0.96366669,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"70","last_page":"77"},"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":0.9997000098228455,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9990000128746033,"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/automatic-summarization","display_name":"Automatic summarization","score":0.9544959664344788},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.8139186501502991},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7770301699638367},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6249960660934448},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.5499347448348999},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4326379895210266},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.07880282402038574}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9544959664344788},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.8139186501502991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7770301699638367},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6249960660934448},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.5499347448348999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4326379895210266},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.07880282402038574},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/w16-1608","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-1608","pdf_url":"https://www.aclweb.org/anthology/W16-1608.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 1st Workshop on Representation Learning for NLP","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w16-1608","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-1608","pdf_url":"https://www.aclweb.org/anthology/W16-1608.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 1st Workshop on Representation Learning for NLP","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1277094987","display_name":null,"funder_award_id":"10044009","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G342704958","display_name":null,"funder_award_id":"funded","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G3514145075","display_name":null,"funder_award_id":"2013R1A2A2A01068687","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G5871052300","display_name":null,"funder_award_id":"2013R1A2A2A01068687","funder_id":"https://openalex.org/F4320322030","funder_display_name":"Ministry of Science, ICT and Future Planning"},{"id":"https://openalex.org/G8582691448","display_name":null,"funder_award_id":"MOTIE, Korea","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G992484961","display_name":null,"funder_award_id":"Korea","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"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/W2963964519.pdf","grobid_xml":"https://content.openalex.org/works/W2963964519.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1899504021","https://openalex.org/W1924770834","https://openalex.org/W1974339500","https://openalex.org/W1978579256","https://openalex.org/W2028418738","https://openalex.org/W2044275678","https://openalex.org/W2066350381","https://openalex.org/W2085625396","https://openalex.org/W2094426896","https://openalex.org/W2103089063","https://openalex.org/W2115613106","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2140679639","https://openalex.org/W2144211451","https://openalex.org/W2150824314","https://openalex.org/W2154652894","https://openalex.org/W2157331557","https://openalex.org/W2280798142","https://openalex.org/W2293771131","https://openalex.org/W2341349540","https://openalex.org/W2741457819","https://openalex.org/W2767096892","https://openalex.org/W2964308564","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W2973759123","https://openalex.org/W1517524280"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"introduce":[4],"temporal":[5,83],"hierarchies":[6,84],"to":[7,10,14,41,58,92],"the":[8,16,30,38,45,59,64,82,87,97],"sequence":[9,11],"(seq2seq)":[12],"model":[13,28,55,69],"tackle":[15],"problem":[17],"of":[18,21,29,47,89,99],"abstractive":[19],"summarization":[20],"scientific":[22],"articles.":[23],"The":[24,53,77],"proposed":[25,54],"Multiple":[26],"Timescale":[27],"Gated":[31],"Recurrent":[32],"Unit":[33],"(MT-GRU)":[34],"is":[35,56],"implemented":[36],"in":[37,50],"encoderdecoder":[39],"setting":[40],"better":[42,95],"deal":[43],"with":[44],"presence":[46,98],"multiple":[48],"compositionalities":[49,94],"larger":[51],"texts.":[52],"compared":[57],"conventional":[60],"RNN":[61],"encoderdecoder,":[62],"and":[63,72],"results":[65,78],"demonstrate":[66],"that":[67,81],"our":[68],"trains":[70],"faster":[71],"shows":[73],"significant":[74],"performance":[75],"gains.":[76],"also":[79],"show":[80],"help":[85],"improve":[86],"ability":[88],"seq2seq":[90],"models":[91],"capture":[93],"without":[96],"highly":[100],"complex":[101],"architectural":[102],"hierarchies.":[103]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":4}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}