{"id":"https://openalex.org/W2890861846","doi":"https://doi.org/10.18653/v1/d18-1442","title":"Iterative Document Representation Learning Towards Summarization with Polishing","display_name":"Iterative Document Representation Learning Towards Summarization with Polishing","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2890861846","doi":"https://doi.org/10.18653/v1/d18-1442","mag":"2890861846"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d18-1442","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1442","pdf_url":"https://www.aclweb.org/anthology/D18-1442.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/D18-1442.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110999110","display_name":"Xiuying Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiuying Chen","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021862101","display_name":"Shen Gao","orcid":"https://orcid.org/0000-0003-1301-3700"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shen Gao","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073065834","display_name":"Chongyang Tao","orcid":"https://orcid.org/0000-0002-4162-2119"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chongyang Tao","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100381754","display_name":"Yan Song","orcid":"https://orcid.org/0000-0002-2849-2962"},"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":"Yan Song","raw_affiliation_strings":["Tencent AI Lab"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037132097","display_name":"Dongyan Zhao","orcid":"https://orcid.org/0000-0002-0396-6703"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongyan Zhao","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100716372","display_name":"Rui Yan","orcid":"https://orcid.org/0000-0002-3356-6823"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Yan","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5110999110"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":4.235,"has_fulltext":true,"cited_by_count":42,"citation_normalized_percentile":{"value":0.95341396,"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":"4088","last_page":"4097"},"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":0.988099992275238,"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":0.9644609689712524},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.841842532157898},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.7025455832481384},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5770571231842041},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.525675356388092},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.519263505935669},{"id":"https://openalex.org/keywords/multi-document-summarization","display_name":"Multi-document summarization","score":0.5092827081680298},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4474859833717346},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.4303137958049774},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4095267951488495},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1193191409111023}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9644609689712524},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.841842532157898},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.7025455832481384},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5770571231842041},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.525675356388092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.519263505935669},{"id":"https://openalex.org/C134714966","wikidata":"https://www.wikidata.org/wiki/Q6934448","display_name":"Multi-document summarization","level":3,"score":0.5092827081680298},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4474859833717346},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.4303137958049774},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4095267951488495},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1193191409111023},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d18-1442","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1442","pdf_url":"https://www.aclweb.org/anthology/D18-1442.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/d18-1442","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1442","pdf_url":"https://www.aclweb.org/anthology/D18-1442.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":[{"score":0.8600000143051147,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2890861846.pdf","grobid_xml":"https://content.openalex.org/works/W2890861846.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W204260652","https://openalex.org/W1522301498","https://openalex.org/W1544827683","https://openalex.org/W1602831581","https://openalex.org/W1660606671","https://openalex.org/W1977884995","https://openalex.org/W2020319149","https://openalex.org/W2027447887","https://openalex.org/W2064675550","https://openalex.org/W2112077341","https://openalex.org/W2126851059","https://openalex.org/W2157331557","https://openalex.org/W2250539671","https://openalex.org/W2293453011","https://openalex.org/W2307381258","https://openalex.org/W2402144811","https://openalex.org/W2515893700","https://openalex.org/W2572589325","https://openalex.org/W2574535369","https://openalex.org/W2606974598","https://openalex.org/W2739672253","https://openalex.org/W2741672218","https://openalex.org/W2788283780","https://openalex.org/W2915816387","https://openalex.org/W2949615363","https://openalex.org/W2951008357","https://openalex.org/W2951777553","https://openalex.org/W2952138241","https://openalex.org/W2953384591","https://openalex.org/W2962762898","https://openalex.org/W2962965405","https://openalex.org/W2962972512","https://openalex.org/W2964121744","https://openalex.org/W3099086015"],"related_works":["https://openalex.org/W3164984162","https://openalex.org/W2104677027","https://openalex.org/W2902627734","https://openalex.org/W2112885393","https://openalex.org/W2173208124","https://openalex.org/W2568827738","https://openalex.org/W1990695371","https://openalex.org/W2365100044","https://openalex.org/W2099859325","https://openalex.org/W2474342320"],"abstract_inverted_index":{"In":[0],"this":[1,65],"paper,":[2],"we":[3,67,88],"introduce":[4,68,90],"Iterative":[5],"Text":[6],"Summarization":[7],"(ITS),":[8],"an":[9,31],"iteration-based":[10],"model":[11,70,107,122],"for":[12,26],"supervised":[13],"extractive":[14,126],"text":[15],"summarization,":[16],"inspired":[17],"by":[18,130,133],"the":[19,74,81,99,106,114],"observation":[20],"that":[21,95,120],"it":[22],"is":[23],"often":[24],"necessary":[25],"a":[27,49,55,60,69,91],"human":[28],"to":[29,37,53,101],"read":[30,47],"article":[32],"multiple":[33],"times":[34],"in":[35,59,105],"order":[36],"fully":[38],"understand":[39],"and":[40,116,132],"summarize":[41],"its":[42],"contents.":[43],"Current":[44],"summarization":[45],"approaches":[46],"through":[48,80],"document":[50,56,75],"only":[51],"once":[52],"generate":[54],"representation,":[57],"resulting":[58],"sub-optimal":[61],"representation.":[62],"To":[63],"address":[64],"issue":[66],"which":[71,102],"iteratively":[72],"polishes":[73],"representation":[76],"on":[77,113],"many":[78],"passes":[79],"document.":[82],"As":[83],"part":[84],"of":[85],"our":[86,121],"model,":[87],"also":[89],"selective":[92],"reading":[93],"mechanism":[94],"decides":[96],"more":[97],"accurately":[98],"extent":[100],"each":[103],"sentence":[104],"should":[108],"be":[109],"updated.":[110],"Experimental":[111],"results":[112],"CNN/DailyMail":[115],"DUC2002":[117],"datasets":[118],"demonstrate":[119],"significantly":[123],"outperforms":[124],"state-of-the-art":[125],"systems":[127],"when":[128],"evaluated":[129],"machines":[131],"humans.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}