{"id":"https://openalex.org/W4411638711","doi":"https://doi.org/10.18653/v1/2024.eacl-short.20","title":"Source Identification in Abstractive Summarization","display_name":"Source Identification in Abstractive Summarization","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4411638711","doi":"https://doi.org/10.18653/v1/2024.eacl-short.20"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2024.eacl-short.20","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.eacl-short.20","pdf_url":"https://aclanthology.org/2024.eacl-short.20.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 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2024.eacl-short.20.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015499848","display_name":"Yoshi Suhara","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoshi Suhara","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5070555838","display_name":"Dimitris Alikaniotis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dimitris Alikaniotis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26284569,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"212","last_page":"224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9973999857902527,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9973999857902527,"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":0.9962999820709229,"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/T10028","display_name":"Topic Modeling","score":0.9948999881744385,"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":0.8983154892921448},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7672666311264038},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.673738420009613},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4682525098323822},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4669210910797119}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8983154892921448},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7672666311264038},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.673738420009613},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4682525098323822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4669210910797119},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2024.eacl-short.20","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.eacl-short.20","pdf_url":"https://aclanthology.org/2024.eacl-short.20.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 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2024.eacl-short.20","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.eacl-short.20","pdf_url":"https://aclanthology.org/2024.eacl-short.20.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 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411638711.pdf","grobid_xml":"https://content.openalex.org/works/W4411638711.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2351187795","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Neural":[0],"abstractive":[1,44,106],"summarization":[2],"models":[3],"make":[4],"summaries":[5,45,61,64],"in":[6,34,104,113],"an":[7],"end-to-end":[8],"manner,":[9],"and":[10,41,62,75,84],"little":[11],"is":[12,19],"known":[13],"about":[14],"how":[15,43],"the":[16,35,50,73,94,99],"source":[17,39,51,57,81],"information":[18,33],"actually":[20],"converted":[21],"into":[22],"summaries.In":[23],"this":[24,53],"paper,":[25],"we":[26,55],"define":[27],"input":[28],"sentences":[29,40,58],"that":[30,98],"contain":[31],"essential":[32],"generated":[36,65],"summary":[37],"as":[38],"study":[42],"are":[46],"made":[47],"by":[48,66],"analyzing":[49],"sentences.To":[52],"end,":[54],"annotate":[56],"for":[59,93],"reference":[60],"system":[63],"PEGASUS":[67],"on":[68],"document-summary":[69],"pairs":[70],"sampled":[71],"from":[72],"CNN/DailyMail":[74],"XSum":[76],"datasets.We":[77],"also":[78],"formulate":[79],"automatic":[80],"sentence":[82],"detection":[83],"compare":[85],"multiple":[86],"methods":[87,110],"to":[88],"establish":[89],"a":[90],"strong":[91],"baseline":[92],"task.Experimental":[95],"results":[96],"show":[97],"perplexity-based":[100],"method":[101],"performs":[102],"well":[103],"highly":[105],"settings,":[107],"while":[108],"similarity-based":[109],"perform":[111],"robustly":[112],"relatively":[114],"extractive":[115],"settings.":[116]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
