{"id":"https://openalex.org/W4307308932","doi":"https://doi.org/10.48550/arxiv.2210.12330","title":"Salience Allocation as Guidance for Abstractive Summarization","display_name":"Salience Allocation as Guidance for Abstractive Summarization","publication_year":2022,"publication_date":"2022-10-22","ids":{"openalex":"https://openalex.org/W4307308932","doi":"https://doi.org/10.48550/arxiv.2210.12330"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2210.12330","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.12330","pdf_url":"https://arxiv.org/pdf/2210.12330","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2210.12330","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100455805","display_name":"Fei Wang","orcid":"https://orcid.org/0000-0002-2212-3947"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wang, Fei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083752471","display_name":"Kaiqiang Song","orcid":"https://orcid.org/0000-0001-8203-9723"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Kaiqiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445028","display_name":"Hongming Zhang","orcid":"https://orcid.org/0000-0001-8172-6484"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Hongming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013438739","display_name":"Lifeng Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Lifeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042006948","display_name":"Sangwoo Cho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cho, Sangwoo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024873469","display_name":"Wenlin Yao","orcid":"https://orcid.org/0000-0002-4502-0350"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Wenlin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100334518","display_name":"Xiaoyang Wang","orcid":"https://orcid.org/0000-0003-4213-0762"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiaoyang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102861481","display_name":"Muhao Chen","orcid":"https://orcid.org/0000-0003-0118-3147"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Muhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5034476404","display_name":"Dong Yu","orcid":"https://orcid.org/0000-0003-0520-6844"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Dong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5100455805"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9993000030517578,"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":0.9911999702453613,"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":0.9829539060592651},{"id":"https://openalex.org/keywords/salience","display_name":"Salience (neuroscience)","score":0.9232006072998047},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.7868641018867493},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.774226188659668},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48622289299964905},{"id":"https://openalex.org/keywords/multi-document-summarization","display_name":"Multi-document summarization","score":0.471040278673172},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4521097242832184},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4122838079929352},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3873150646686554}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9829539060592651},{"id":"https://openalex.org/C108154423","wikidata":"https://www.wikidata.org/wiki/Q1469792","display_name":"Salience (neuroscience)","level":2,"score":0.9232006072998047},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.7868641018867493},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.774226188659668},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48622289299964905},{"id":"https://openalex.org/C134714966","wikidata":"https://www.wikidata.org/wiki/Q6934448","display_name":"Multi-document summarization","level":3,"score":0.471040278673172},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4521097242832184},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4122838079929352},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3873150646686554},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2210.12330","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.12330","pdf_url":"https://arxiv.org/pdf/2210.12330","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2210.12330","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2210.12330","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2210.12330","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.12330","pdf_url":"https://arxiv.org/pdf/2210.12330","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.49000000953674316,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4307308932","https://openalex.org/W2323464168","https://openalex.org/W2996124973","https://openalex.org/W3164984162","https://openalex.org/W2089705257","https://openalex.org/W2104677027","https://openalex.org/W2902627734","https://openalex.org/W4383427356","https://openalex.org/W4235368871","https://openalex.org/W2949519365"],"abstract_inverted_index":{"Abstractive":[0,110],"summarization":[1,22,94,122],"models":[2,23],"typically":[3],"learn":[4],"to":[5,24,44,55,73,119,126],"capture":[6],"the":[7,61,85,114,141],"salient":[8,28],"information":[9,45],"from":[10],"scratch":[11],"implicitly.":[12],"Recent":[13],"literature":[14],"adds":[15],"extractive":[16,35],"summaries":[17,36],"as":[18,37,107],"guidance":[19,38],"for":[20,109,163,171],"abstractive":[21,121],"provide":[25],"hints":[26],"of":[27,65,116],"content":[29,67,80],"and":[30,63,99,123,132,146],"achieves":[31],"better":[32],"performance.":[33],"However,":[34],"could":[39],"be":[40,82],"over":[41],"strict,":[42],"leading":[43],"loss":[46],"or":[47],"noisy":[48],"signals.":[49],"Furthermore,":[50],"it":[51,70],"cannot":[52],"easily":[53],"adapt":[54],"documents":[56],"with":[57,96],"various":[58],"abstractiveness.":[59,130],"As":[60],"number":[62],"allocation":[64,115],"salience":[66,101,117,161],"pieces":[68],"vary,":[69],"is":[71,144],"hard":[72],"find":[74],"a":[75,92,97,158,168],"fixed":[76],"threshold":[77],"deciding":[78],"which":[79],"should":[81],"included":[83],"in":[84,128],"guidance.":[86],"In":[87],"this":[88],"paper,":[89],"we":[90],"propose":[91],"novel":[93],"approach":[95],"flexible":[98],"reliable":[100],"guidance,":[102],"namely":[103],"SEASON":[104,112],"(SaliencE":[105],"Allocation":[106],"Guidance":[108],"SummarizatiON).":[111],"utilizes":[113],"expectation":[118],"guide":[120],"adapts":[124],"well":[125],"articles":[127,156],"different":[129],"Automatic":[131],"human":[133],"evaluations":[134],"on":[135,150],"two":[136],"benchmark":[137],"datasets":[138],"show":[139],"that":[140],"proposed":[142],"method":[143],"effective":[145],"reliable.":[147],"Empirical":[148],"results":[149],"more":[151],"than":[152],"one":[153],"million":[154],"news":[155,164,173],"demonstrate":[157],"natural":[159],"fifteen-fifty":[160],"split":[162],"article":[165],"sentences,":[166],"providing":[167],"useful":[169],"insight":[170],"composing":[172],"articles.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}