{"id":"https://openalex.org/W2953313262","doi":"https://doi.org/10.18653/v1/p19-1099","title":"Global Optimization under Length Constraint for Neural Text Summarization","display_name":"Global Optimization under Length Constraint for Neural Text Summarization","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2953313262","doi":"https://doi.org/10.18653/v1/p19-1099","mag":"2953313262"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1099","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1099","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 57th Annual Meeting of the Association for Computational Linguistics","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/p19-1099","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109580043","display_name":"Takuya Makino","orcid":"https://orcid.org/0009-0008-3639-1636"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Takuya Makino","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050899086","display_name":"Tomoya Iwakura","orcid":"https://orcid.org/0000-0002-6558-4911"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tomoya Iwakura","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042127858","display_name":"Hiroya Takamura","orcid":"https://orcid.org/0000-0002-3244-8294"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hiroya Takamura","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5035876897","display_name":"Manabu Okumura","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manabu Okumura","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5109580043"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9204,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.94933892,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1039","last_page":"1048"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9651724100112915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7136565446853638},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.6608147621154785},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.552057683467865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5384604334831238},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3329823613166809},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12820574641227722},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.05951783061027527}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9651724100112915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7136565446853638},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.6608147621154785},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.552057683467865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5384604334831238},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3329823613166809},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12820574641227722},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.05951783061027527},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1099","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1099","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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1099","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1099","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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W23242996","https://openalex.org/W1591706642","https://openalex.org/W2028339364","https://openalex.org/W2081265723","https://openalex.org/W2081388731","https://openalex.org/W2103164118","https://openalex.org/W2108563286","https://openalex.org/W2146574666","https://openalex.org/W2154652894","https://openalex.org/W2251656952","https://openalex.org/W2467173223","https://openalex.org/W2567525733","https://openalex.org/W2606974598","https://openalex.org/W2609482285","https://openalex.org/W2612675303","https://openalex.org/W2735492478","https://openalex.org/W2788139998","https://openalex.org/W2798542795","https://openalex.org/W2890868349","https://openalex.org/W2890914727","https://openalex.org/W2962805889","https://openalex.org/W2962944953","https://openalex.org/W2962965405","https://openalex.org/W2962985882","https://openalex.org/W2963104691","https://openalex.org/W2963248296","https://openalex.org/W2963463964","https://openalex.org/W2963676814","https://openalex.org/W2963768805","https://openalex.org/W2964121744","https://openalex.org/W2964165364","https://openalex.org/W2964265128"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W1517524280","https://openalex.org/W4323520239","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"We":[0,35,123],"propose":[1],"a":[2,32,42,46,54,71],"global":[3],"optimization":[4,40,121],"method":[5],"under":[6],"length":[7,145],"constraint":[8],"(GOLC)":[9],"for":[10,134],"neural":[11,73],"text":[12],"summarization":[13,58,74],"models.":[14],"GOLC":[15,37,78],"increases":[16],"the":[17,85,104,119,126,129,137],"probabilities":[18],"of":[19,61,100,128,131,161],"generating":[20],"summaries":[21,82,92,133],"that":[22,70,140],"have":[23],"high":[24],"evaluation":[25],"scores,":[26],"ROUGE":[27],"in":[28],"this":[29],"paper,":[30],"within":[31],"desired":[33],"length.":[34],"compared":[36,102],"with":[38,77,118,136,143],"two":[39],"methods,":[41],"maximum":[43],"log-likelihood":[44],"and":[45,53,95,112],"minimum":[47],"risk":[48],"training,":[49],"on":[50,93,97,109,116],"CNN/Daily":[51,94,110],"Mail":[52,111],"Japanese":[55],"single":[56],"document":[57],"data":[59],"set":[60],"The":[62,66,147],"Mainichi":[63,117],"Shimbun":[64],"Newspapers.":[65],"experimental":[67],"results":[68,150],"show":[69,151],"state-of-the-art":[72],"model":[75],"optimized":[76],"generates":[79],"fewer":[80],"overlength":[81,91],"while":[83],"maintaining":[84],"fastest":[86],"processing":[87],"speed;":[88],"only":[89],"6.70%":[90],"7.8%":[96],"long":[98],"summary":[99],"Mainichi,":[101],"to":[103,107,114,154],"approximately":[105,152],"20%":[106],"50%":[108],"10%":[113],"30%":[115,153],"other":[120],"methods.":[122],"also":[124],"demonstrate":[125],"importance":[127],"generation":[130],"in-length":[132,162],"post-editing":[135,157],"dataset":[138],"Mainich":[139],"is":[141],"created":[142],"strict":[144],"constraints.":[146],"ex-":[148],"perimental":[149],"40%":[155],"improved":[156],"time":[158],"by":[159],"use":[160],"summaries.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}