{"id":"https://openalex.org/W3152821919","doi":"https://doi.org/10.18653/v1/2021.eacl-main.22","title":"AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization","display_name":"AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3152821919","doi":"https://doi.org/10.18653/v1/2021.eacl-main.22","mag":"3152821919"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2021.eacl-main.22","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2021.eacl-main.22","pdf_url":"https://aclanthology.org/2021.eacl-main.22.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 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2021.eacl-main.22.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040708820","display_name":"Keping Bi","orcid":"https://orcid.org/0000-0001-5123-4999"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keping Bi","raw_affiliation_strings":["University of Massachusetts Amherst,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst,","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055937996","display_name":"Rahul Jha","orcid":"https://orcid.org/0000-0002-5641-4347"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Rahul Jha","raw_affiliation_strings":["Microsoft,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft,","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067236943","display_name":"Bruce Croft","orcid":null},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Bruce Croft","raw_affiliation_strings":["University of Massachusetts Amherst,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst,","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030468199","display_name":"Asl\u0131 \u00c7eliky\u0131lmaz","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Asli Celikyilmaz","raw_affiliation_strings":["Microsoft Research AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research AI","institution_ids":["https://openalex.org/I4210164937"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067236943"],"corresponding_institution_ids":["https://openalex.org/I24603500"],"apc_list":null,"apc_paid":null,"fwci":2.9306,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.92813905,"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":"281","last_page":"291"},"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":0.9972000122070312,"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":0.8051929473876953},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7966174483299255},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6962488293647766},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.6613339781761169},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6397579908370972},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5613470077514648},{"id":"https://openalex.org/keywords/salience","display_name":"Salience (neuroscience)","score":0.5392173528671265},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4332336187362671},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.41921207308769226},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36920490860939026}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8051929473876953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7966174483299255},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6962488293647766},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.6613339781761169},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6397579908370972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5613470077514648},{"id":"https://openalex.org/C108154423","wikidata":"https://www.wikidata.org/wiki/Q1469792","display_name":"Salience (neuroscience)","level":2,"score":0.5392173528671265},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4332336187362671},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.41921207308769226},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36920490860939026},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2021.eacl-main.22","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2021.eacl-main.22","pdf_url":"https://aclanthology.org/2021.eacl-main.22.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 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2021.eacl-main.22","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2021.eacl-main.22","pdf_url":"https://aclanthology.org/2021.eacl-main.22.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 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3152821919.pdf","grobid_xml":"https://content.openalex.org/works/W3152821919.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W1525595230","https://openalex.org/W1544827683","https://openalex.org/W1973435495","https://openalex.org/W1973894278","https://openalex.org/W1977593346","https://openalex.org/W2017187090","https://openalex.org/W2083305840","https://openalex.org/W2083778364","https://openalex.org/W2101390659","https://openalex.org/W2140440594","https://openalex.org/W2144933361","https://openalex.org/W2152992673","https://openalex.org/W2154652894","https://openalex.org/W2251911042","https://openalex.org/W2307381258","https://openalex.org/W2573170368","https://openalex.org/W2574535369","https://openalex.org/W2606974598","https://openalex.org/W2612675303","https://openalex.org/W2735674392","https://openalex.org/W2890419630","https://openalex.org/W2896457183","https://openalex.org/W2896807716","https://openalex.org/W2949615363","https://openalex.org/W2952138241","https://openalex.org/W2962785754","https://openalex.org/W2962972512","https://openalex.org/W2963125472","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963607157","https://openalex.org/W2964028111","https://openalex.org/W2970419734","https://openalex.org/W3015015255","https://openalex.org/W3034353423","https://openalex.org/W3101913037","https://openalex.org/W3101997094","https://openalex.org/W3138773240","https://openalex.org/W3158986179","https://openalex.org/W4302313152","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2347941600","https://openalex.org/W2401226416","https://openalex.org/W4288796577","https://openalex.org/W3015015255","https://openalex.org/W2011304691","https://openalex.org/W2579653291","https://openalex.org/W159132833","https://openalex.org/W2251823567","https://openalex.org/W2125780880","https://openalex.org/W3000193055"],"abstract_inverted_index":{"Redundancy-aware":[0],"extractive":[1,157],"summarization":[2,158],"systems":[3],"score":[4],"the":[5,8,33,52,66,74,83,121,124],"redundancy":[6,62],"of":[7,35,68,123,126],"sentences":[9,40],"to":[10,56,115],"be":[11],"included":[12],"in":[13,142],"a":[14,106,143],"summary":[15,76],"either":[16],"jointly":[17,36,97],"with":[18,41],"their":[19],"salience":[20,69,99,111,117],"information":[21],"or":[22,60],"separately":[23],"as":[24,153,155],"an":[25],"additional":[26],"sentence":[27,103],"scoring":[28,37],"step.":[29],"Previous":[30],"work":[31],"shows":[32],"efficacy":[34],"and":[38,100,105,118,133],"selecting":[39],"neural":[42],"sequence":[43],"generation":[44],"models.":[45],"It":[46],"is,":[47],"however,":[48],"not":[49,78],"well-understood":[50],"if":[51],"gain":[53],"is":[54,77],"due":[55],"better":[57,61,149],"encoding":[58,85],"techniques":[59],"reduction":[63],"approaches.":[64],"Similarly,":[65],"contribution":[67],"versus":[70],"diversity":[71,140],"components":[72],"on":[73,82,131],"created":[75],"studied":[79],"well.":[80],"Building":[81],"state-of-the-art":[84,156],"methods":[86],"for":[87],"summarization,":[88],"we":[89],"present":[90],"two":[91],"adaptive":[92],"learning":[93],"models:":[94],"AREDSUM-SEQ":[95,152],"that":[96,109,137],"considers":[98],"novelty":[101],"during":[102],"selection;":[104],"two-step":[107],"AREDSUM-CTX":[108,146],"scores":[110],"first,":[112],"then":[113],"learns":[114],"balance":[116],"redundancy,":[119],"enabling":[120],"measurement":[122],"impact":[125],"each":[127],"aspect.":[128],"Empirical":[129],"results":[130],"CNN/DailyMail":[132],"NYT50":[134],"datasets":[135],"show":[136],"by":[138],"modeling":[139],"explicitly":[141],"separate":[144],"step,":[145],"achieves":[147],"significantly":[148],"performance":[150],"than":[151],"well":[154],"baselines.":[159]},"counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}