{"id":"https://openalex.org/W2467173223","doi":"https://doi.org/10.18653/v1/n16-1012","title":"Abstractive Sentence Summarization with Attentive Recurrent Neural Networks","display_name":"Abstractive Sentence Summarization with Attentive Recurrent Neural Networks","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2467173223","doi":"https://doi.org/10.18653/v1/n16-1012","mag":"2467173223"},"language":"en","primary_location":{"id":"doi:10.18653/v1/n16-1012","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/n16-1012","pdf_url":"https://www.aclweb.org/anthology/N16-1012.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 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","raw_type":"proceedings-article"},"type":"conference-abstract","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/N16-1012.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078511139","display_name":"Sumit Chopra","orcid":"https://orcid.org/0009-0009-6637-2230"},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Sumit Chopra","raw_affiliation_strings":["Facebook AI Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook AI Research","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083212922","display_name":"Michael Auli","orcid":"https://orcid.org/0000-0001-5974-4459"},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Michael Auli","raw_affiliation_strings":["Facebook AI Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook AI Research","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062546146","display_name":"Alexander M. Rush","orcid":"https://orcid.org/0000-0002-9900-1606"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alexander M. Rush","raw_affiliation_strings":["Harvard SEAS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard SEAS","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":933,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"93","last_page":"98"},"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":0.9998999834060669,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9991000294685364,"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":0.9163882732391357},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8066278100013733},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6943107843399048},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6352818608283997},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.557489812374115},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.542492151260376},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3922445476055145}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9163882732391357},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8066278100013733},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6943107843399048},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6352818608283997},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.557489812374115},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.542492151260376},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3922445476055145}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/n16-1012","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/n16-1012","pdf_url":"https://www.aclweb.org/anthology/N16-1012.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 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/n16-1012","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/n16-1012","pdf_url":"https://www.aclweb.org/anthology/N16-1012.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 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2467173223.pdf","grobid_xml":"https://content.openalex.org/works/W2467173223.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1498416817","https://openalex.org/W1902237438","https://openalex.org/W1964326564","https://openalex.org/W2028339364","https://openalex.org/W2056609756","https://openalex.org/W2083451366","https://openalex.org/W2103164118","https://openalex.org/W2104944827","https://openalex.org/W2110485445","https://openalex.org/W2115322217","https://openalex.org/W2115937944","https://openalex.org/W2133182690","https://openalex.org/W2133564696","https://openalex.org/W2146574666","https://openalex.org/W2154652894","https://openalex.org/W2156422881","https://openalex.org/W2157331557","https://openalex.org/W2163117351","https://openalex.org/W2251654079","https://openalex.org/W2251656952","https://openalex.org/W2280798142","https://openalex.org/W2293778248","https://openalex.org/W2950635152","https://openalex.org/W2962965405","https://openalex.org/W4254816979"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W3148229873","https://openalex.org/W4242223894","https://openalex.org/W2091301346","https://openalex.org/W2150160875","https://openalex.org/W1517524280","https://openalex.org/W4306886878","https://openalex.org/W4323520239","https://openalex.org/W3111372071"],"abstract_inverted_index":{"Abstractive":[0],"Sentence":[1],"Summarization":[2],"generates":[3,26],"a":[4,8,19,27,38],"shorter":[5],"version":[6],"of":[7,29,57],"given":[9],"sentence":[10],"while":[11,96],"attempting":[12],"to":[13,69],"preserve":[14],"its":[15],"meaning.":[16],"We":[17],"introduce":[18],"conditional":[20],"recurrent":[21],"neural":[22],"network":[23],"(RNN)":[24],"which":[25,43],"summary":[28],"an":[30,72],"input":[31,52],"sentence.":[32],"The":[33],"conditioning":[34],"is":[35,67],"provided":[36],"by":[37],"novel":[39],"convolutional":[40],"attention-based":[41],"encoder":[42],"ensures":[44],"that":[45,82],"the":[46,50,83,87,93,100],"decoder":[47],"focuses":[48],"on":[49,63,75,92,99],"appropriate":[51],"words":[53],"at":[54],"each":[55],"step":[56],"generation.":[58],"Our":[59,79],"model":[60,84],"relies":[61],"only":[62],"learned":[64],"features":[65],"and":[66],"easy":[68],"train":[70],"in":[71],"end-to-end":[73],"fashion":[74],"large":[76],"data":[77],"sets.":[78],"experiments":[80],"show":[81],"significantly":[85],"outperforms":[86],"recently":[88],"proposed":[89],"state-of-the-art":[90],"method":[91],"Gigaword":[94],"corpus":[95],"performing":[97],"competitively":[98],"DUC-2004":[101],"shared":[102],"task.":[103]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":49},{"year":2023,"cited_by_count":82},{"year":2022,"cited_by_count":90},{"year":2021,"cited_by_count":126},{"year":2020,"cited_by_count":144},{"year":2019,"cited_by_count":191},{"year":2018,"cited_by_count":150},{"year":2017,"cited_by_count":53},{"year":2016,"cited_by_count":14}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}