{"id":"https://openalex.org/W7155220854","doi":"https://doi.org/10.48550/arxiv.2604.19185","title":"SCURank: Ranking Multiple Candidate Summaries with Summary Content Units for Enhanced Summarization","display_name":"SCURank: Ranking Multiple Candidate Summaries with Summary Content Units for Enhanced Summarization","publication_year":2026,"publication_date":"2026-04-21","ids":{"openalex":"https://openalex.org/W7155220854","doi":"https://doi.org/10.48550/arxiv.2604.19185"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.19185","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19185","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.19185","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001802403","display_name":"Bo-Jyun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wang, Bo-Jyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040237383","display_name":"Ying-Jia Lin","orcid":"https://orcid.org/0000-0003-4347-0232"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Ying-Jia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134306741","display_name":"Hung-Yu Kao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kao, Hung-Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5001802403"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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":0.8744999766349792,"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":0.8744999766349792,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.017100000753998756,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.010099999606609344,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.8988999724388123},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7626000046730042},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.652999997138977},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5253999829292297},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.47450000047683716},{"id":"https://openalex.org/keywords/multi-document-summarization","display_name":"Multi-document summarization","score":0.4643999934196472},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.43959999084472656}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8988999724388123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8119999766349792},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7626000046730042},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.652999997138977},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5918999910354614},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5253999829292297},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.47450000047683716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46639999747276306},{"id":"https://openalex.org/C134714966","wikidata":"https://www.wikidata.org/wiki/Q6934448","display_name":"Multi-document summarization","level":3,"score":0.4643999934196472},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.43959999084472656},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3865000009536743},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35749998688697815},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3515999913215637},{"id":"https://openalex.org/C124975894","wikidata":"https://www.wikidata.org/wiki/Q7293290","display_name":"Ranking SVM","level":3,"score":0.33059999346733093},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.2662000060081482}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.19185","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19185","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.19185","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19185","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Small":[0],"language":[1,14],"models":[2,15],"(SLMs),":[3],"such":[4],"as":[5],"BART,":[6],"can":[7],"achieve":[8],"summarization":[9,52],"performance":[10],"comparable":[11],"to":[12,37],"large":[13],"(LLMs)":[16],"via":[17],"distillation.":[18,136],"However,":[19],"existing":[20],"LLM-based":[21,103],"ranking":[22,104,133],"strategies":[23],"for":[24,139],"summary":[25],"candidates":[26],"suffer":[27],"from":[28,90],"instability,":[29],"while":[30],"classical":[31],"metrics":[32,101],"(e.g.,":[33],"ROUGE)":[34],"are":[35],"insufficient":[36],"rank":[38],"high-quality":[39],"summaries.":[40],"To":[41],"address":[42],"these":[43],"issues,":[44],"we":[45],"introduce":[46],"\\textbf{SCURank},":[47],"a":[48],"framework":[49],"that":[50,97,115],"enhances":[51,120],"by":[53],"leveraging":[54],"\\textbf{Summary":[55],"Content":[56],"Units":[57],"(SCUs)}.":[58],"Instead":[59],"of":[60,78,85,131],"relying":[61],"on":[62,72],"unstable":[63],"comparisons":[64],"or":[65],"surface-level":[66],"overlap,":[67],"SCURank":[68,86,98,140],"evaluates":[69],"summaries":[70,89,119],"based":[71],"the":[73,83,129],"richness":[74],"and":[75,102,109,123],"semantic":[76],"importance":[77],"information":[79],"content.":[80],"We":[81],"investigate":[82],"effectiveness":[84],"in":[87,134],"distilling":[88],"multiple":[91],"diverse":[92,117],"LLMs.":[93],"Experimental":[94],"results":[95],"demonstrate":[96],"outperforms":[99],"traditional":[100],"methods":[105],"across":[106],"evaluation":[107],"measures":[108],"datasets.":[110],"Furthermore,":[111],"our":[112],"findings":[113],"show":[114],"incorporating":[116],"LLM":[118],"model":[121,126],"abstractiveness":[122],"overall":[124],"distilled":[125],"performance,":[127],"validating":[128],"benefits":[130],"information-centric":[132],"multi-LLM":[135],"The":[137],"code":[138],"is":[141],"available":[142],"at":[143],"https://github.com/IKMLab/SCURank.":[144]},"counts_by_year":[],"updated_date":"2026-04-23T06:20:18.424754","created_date":"2026-04-23T00:00:00"}