{"id":"https://openalex.org/W2964165364","doi":"https://doi.org/10.18653/v1/p16-1154","title":"Incorporating Copying Mechanism in Sequence-to-Sequence Learning","display_name":"Incorporating Copying Mechanism in Sequence-to-Sequence Learning","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2964165364","doi":"https://doi.org/10.18653/v1/p16-1154","mag":"2964165364"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p16-1154","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1154","pdf_url":null,"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":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.18653/v1/p16-1154","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112542984","display_name":"Jiatao Gu","orcid":"https://orcid.org/0000-0003-3578-2711"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jiatao Gu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084830556","display_name":"Zhengdong Lu","orcid":"https://orcid.org/0000-0002-6418-6030"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhengdong Lu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455135","display_name":"Hang Li","orcid":"https://orcid.org/0000-0002-3464-3245"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hang Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056877599","display_name":"Victor O. K. Li","orcid":"https://orcid.org/0000-0002-1380-9445"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Victor O.K. Li","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112542984"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":244.7217,"has_fulltext":false,"cited_by_count":1432,"citation_normalized_percentile":{"value":0.99984297,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1631","last_page":"1640"},"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":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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9986000061035156,"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/copying","display_name":"Copying","score":0.7993576526641846},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.7766884565353394},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6619774699211121},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.6484296321868896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4241476058959961},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.07652491331100464},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.06787097454071045}],"concepts":[{"id":"https://openalex.org/C2779151265","wikidata":"https://www.wikidata.org/wiki/Q1156791","display_name":"Copying","level":2,"score":0.7993576526641846},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.7766884565353394},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6619774699211121},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.6484296321868896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4241476058959961},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.07652491331100464},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.06787097454071045},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p16-1154","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1154","pdf_url":null,"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"}],"best_oa_location":{"id":"doi:10.18653/v1/p16-1154","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1154","pdf_url":null,"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":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1518951372","https://openalex.org/W1591706642","https://openalex.org/W2064675550","https://openalex.org/W2118434577","https://openalex.org/W2130942839","https://openalex.org/W2154652894","https://openalex.org/W2157331557","https://openalex.org/W2194775991","https://openalex.org/W2195405088","https://openalex.org/W2507756961","https://openalex.org/W2950527759","https://openalex.org/W2950898700","https://openalex.org/W2951777553","https://openalex.org/W2962944953","https://openalex.org/W2962965405","https://openalex.org/W2962996600","https://openalex.org/W2963069010","https://openalex.org/W2963963856","https://openalex.org/W2964308564"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4308771405","https://openalex.org/W2355873265","https://openalex.org/W2963669501","https://openalex.org/W3080197661","https://openalex.org/W4318471783","https://openalex.org/W2760667490","https://openalex.org/W2991781269","https://openalex.org/W775724729","https://openalex.org/W2137489486"],"abstract_inverted_index":{"We":[0],"address":[1],"an":[2],"important":[3],"problem":[4],"in":[5,13,17,24,33,49,57,103,115,125],"sequence-to-sequence":[6],"(Seq2Seq)":[7],"learning":[8,82],"referred":[9],"to":[10,41,55,65,68],"as":[11],"copying,":[12],"which":[14,111],"certain":[15],"segments":[16],"the":[18,25,70,97,104,107,116,126,143],"input":[19,117],"sequence":[20,118],"are":[21],"selectively":[22],"replicated":[23],"output":[26,127],"sequence.":[27,128],"A":[28],"similar":[29],"phenomenon":[30],"is":[31,59,63],"observable":[32],"human":[34],"language":[35],"communication.":[36],"For":[37,147],"example,":[38,148],"humans":[39],"tend":[40],"repeat":[42],"entity":[43],"names":[44],"or":[45],"even":[46],"long":[47],"phrases":[48],"conversation.":[50],"The":[51],"challenge":[52],"with":[53,90,106,155],"regard":[54],"copying":[56,77,109],"Seq2Seq":[58,81],"that":[60],"new":[61,86,108],"machinery":[62],"needed":[64],"decide":[66],"when":[67],"perform":[69],"operation.":[71],"In":[72],"this":[73],"paper,":[74],"we":[75],"incorporate":[76],"into":[78],"neural":[79],"network-based":[80],"and":[83,119,137],"propose":[84],"a":[85],"model":[87,154],"called":[88],"CopyNet":[89,93,149],"encoder-decoder":[91],"structure.":[92],"can":[94,112,150],"nicely":[95],"integrate":[96],"regular":[98,152],"way":[99],"of":[100,145],"word":[101],"generation":[102],"decoder":[105],"mechanism":[110],"choose":[113],"sub-sequences":[114],"put":[120],"them":[121],"at":[122],"proper":[123],"places":[124],"Our":[129],"empirical":[130],"study":[131],"on":[132,158],"both":[133],"synthetic":[134],"data":[135,140],"sets":[136,141],"real":[138],"world":[139],"demonstrates":[142],"efficacy":[144],"CopyNet.":[146],"outperform":[151],"RNN-based":[153],"remarkable":[156],"margins":[157],"text":[159],"summarization":[160],"tasks.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":31},{"year":2024,"cited_by_count":74},{"year":2023,"cited_by_count":99},{"year":2022,"cited_by_count":158},{"year":2021,"cited_by_count":230},{"year":2020,"cited_by_count":282},{"year":2019,"cited_by_count":329},{"year":2018,"cited_by_count":147},{"year":2017,"cited_by_count":63},{"year":2016,"cited_by_count":15}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}
