{"id":"https://openalex.org/W2964032708","doi":"https://doi.org/10.24963/ijcai.2018/619","title":"A Reinforced Topic-Aware Convolutional Sequence-to-Sequence Model for Abstractive Text Summarization","display_name":"A Reinforced Topic-Aware Convolutional Sequence-to-Sequence Model for Abstractive Text Summarization","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2964032708","doi":"https://doi.org/10.24963/ijcai.2018/619","mag":"2964032708"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2018/619","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/619","pdf_url":"https://www.ijcai.org/proceedings/2018/0619.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2018/0619.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100336197","display_name":"Li Wang","orcid":"https://orcid.org/0000-0003-2165-0080"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Wang","raw_affiliation_strings":["Tencent Data Center of SNG"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Data Center of SNG","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101821408","display_name":"Junlin Yao","orcid":"https://orcid.org/0000-0003-1958-6913"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Junlin Yao","raw_affiliation_strings":["ETH Z\u00fcrich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Z\u00fcrich","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005542105","display_name":"Yunzhe Tao","orcid":"https://orcid.org/0000-0001-5819-5304"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunzhe Tao","raw_affiliation_strings":["Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100664779","display_name":"Zhong Li","orcid":"https://orcid.org/0000-0002-3849-3416"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhong","raw_affiliation_strings":["Tencent Data Center of SNG"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Data Center of SNG","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100431792","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0002-3865-8145"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Tencent AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056115552","display_name":"Qiang Du","orcid":"https://orcid.org/0000-0002-1067-8937"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiang Du","raw_affiliation_strings":["Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100336197"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":14.0584,"has_fulltext":true,"cited_by_count":127,"citation_normalized_percentile":{"value":0.98990741,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4453","last_page":"4460"},"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":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":0.9983000159263611,"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":0.9236437082290649},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8326257467269897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7124768495559692},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6168370842933655},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6140821576118469},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.5516543984413147},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5391941070556641},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.496479332447052},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.49253591895103455},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43795615434646606},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35154104232788086}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9236437082290649},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8326257467269897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7124768495559692},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6168370842933655},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6140821576118469},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.5516543984413147},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5391941070556641},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.496479332447052},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.49253591895103455},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43795615434646606},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35154104232788086},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2018/619","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/619","pdf_url":"https://www.ijcai.org/proceedings/2018/0619.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2018/619","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/619","pdf_url":"https://www.ijcai.org/proceedings/2018/0619.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964032708.pdf","grobid_xml":"https://content.openalex.org/works/W2964032708.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W104184427","https://openalex.org/W105687093","https://openalex.org/W1880262756","https://openalex.org/W1890230307","https://openalex.org/W2012561700","https://openalex.org/W2016589492","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2154652894","https://openalex.org/W2157331557","https://openalex.org/W2176263492","https://openalex.org/W2280798142","https://openalex.org/W2467173223","https://openalex.org/W2521114121","https://openalex.org/W2536575466","https://openalex.org/W2567070169","https://openalex.org/W2609482285","https://openalex.org/W2612675303","https://openalex.org/W2613904329","https://openalex.org/W2962965405","https://openalex.org/W2962996600","https://openalex.org/W2963084599","https://openalex.org/W2963929190","https://openalex.org/W2964165364"],"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/W2133478886"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,53],"deep":[6],"learning":[7],"approach":[8,42],"to":[9,36,73],"tackle":[10],"the":[11,20,59,68,74,81,89,96,106,113],"automatic":[12],"summarization":[13],"tasks":[14],"by":[15],"incorporating":[16],"topic":[17],"information":[18],"into":[19],"convolutional":[21],"sequence-to-sequence":[22],"(ConvS2S)":[23],"model":[24,70],"and":[25,38,47,99],"using":[26],"self-critical":[27],"sequence":[28],"training":[29],"(SCST)":[30],"for":[31],"optimization.":[32],"Through":[33],"jointly":[34],"attending":[35],"topics":[37],"word-level":[39],"alignment,":[40],"our":[41,109],"can":[43],"improve":[44],"coherence,":[45],"diversity,":[46],"informativeness":[48],"of":[49,108],"generated":[50],"summaries":[51],"via":[52],"biased":[54],"probability":[55],"generation":[56],"mechanism.":[57],"On":[58],"other":[60],"hand,":[61],"reinforcement":[62],"training,":[63],"like":[64],"SCST,":[65],"directly":[66],"optimizes":[67],"proposed":[69,110],"with":[71,92],"respect":[72],"non-differentiable":[75],"metric":[76],"ROUGE,":[77],"which":[78],"also":[79],"avoids":[80],"exposure":[82],"bias":[83],"during":[84],"inference.":[85],"We":[86],"carry":[87],"out":[88],"experimental":[90],"evaluation":[91],"state-of-the-art":[93],"methods":[94],"over":[95],"Gigaword,":[97],"DUC-2004,":[98],"LCSTS":[100],"datasets.":[101],"The":[102],"empirical":[103],"results":[104],"demonstrate":[105],"superiority":[107],"method":[111],"in":[112],"abstractive":[114],"summarization.":[115]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":31},{"year":2020,"cited_by_count":23},{"year":2019,"cited_by_count":24},{"year":2018,"cited_by_count":5}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}