{"id":"https://openalex.org/W7140172529","doi":"https://doi.org/10.48550/arxiv.2603.22103","title":"Multiperspectivity as a Resource for Narrative Similarity Prediction","display_name":"Multiperspectivity as a Resource for Narrative Similarity Prediction","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7140172529","doi":"https://doi.org/10.48550/arxiv.2603.22103"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.22103","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22103","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.2603.22103","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Upravitelev, Max","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Upravitelev, Max","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Solopova, Veronika","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Solopova, Veronika","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yang, Jing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Jakob, Charlott","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jakob, Charlott","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Sahitaj, Premtim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sahitaj, Premtim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Sahitaj, Ariana","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sahitaj, Ariana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Schmitt, Vera","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schmitt, Vera","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"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/T14074","display_name":"Persona Design and Applications","score":0.8299000263214111,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T14074","display_name":"Persona Design and Applications","score":0.8299000263214111,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.022199999541044235,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.012299999594688416,"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/benchmark","display_name":"Benchmark (surveying)","score":0.545199990272522},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5374000072479248},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.531499981880188},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4837999939918518},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.43549999594688416},{"id":"https://openalex.org/keywords/narrative","display_name":"Narrative","score":0.4277999997138977},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.398499995470047},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.39660000801086426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6371999979019165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.59579998254776},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5532000064849854},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.545199990272522},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5374000072479248},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.531499981880188},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48100000619888306},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.43549999594688416},{"id":"https://openalex.org/C199033989","wikidata":"https://www.wikidata.org/wiki/Q1318295","display_name":"Narrative","level":2,"score":0.4277999997138977},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.39660000801086426},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3928000032901764},{"id":"https://openalex.org/C2776119841","wikidata":"https://www.wikidata.org/wiki/Q837675","display_name":"Jury","level":2,"score":0.37299999594688416},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.37070000171661377},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.34599998593330383},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.32100000977516174},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.31060001254081726},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.29499998688697815},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.2915000021457672},{"id":"https://openalex.org/C313442","wikidata":"https://www.wikidata.org/wiki/Q778556","display_name":"Persona","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2709999978542328},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.26739999651908875},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.22103","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22103","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.2603.22103","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22103","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":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.4145999848842621}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Predicting":[0],"narrative":[1],"similarity":[2,26],"can":[3,19],"be":[4],"understood":[5],"as":[6,47],"an":[7,71,103],"inherently":[8],"interpretive":[9,82,149,186],"task:":[10],"different,":[11],"equally":[12],"valid":[13,168],"readings":[14],"of":[15,62,73,106],"the":[16,58,94,100,165,172,178],"same":[17],"text":[18],"produce":[20,128],"divergent":[21],"interpretations":[22,169],"and":[23,151],"thus":[24],"different":[25],"judgments,":[27],"posing":[28],"a":[29,38,48,143],"fundamental":[30],"challenge":[31,49],"for":[32,164,180,185],"semantic":[33],"evaluation":[34,181],"benchmarks":[35],"that":[36,183],"encode":[37],"single":[39],"ground":[40,173],"truth.":[41,174],"Rather":[42],"than":[43],"treating":[44],"this":[45,67],"multiperspectivity":[46],"to":[50,54,84,160],"overcome,":[51],"we":[52,69],"propose":[53],"incorporate":[55],"it":[56],"in":[57],"decision":[59],"making":[60],"process":[61],"predictive":[63],"systems.":[64],"To":[65],"explore":[66],"strategy,":[68],"created":[70],"ensemble":[72,111,134],"31":[74],"LLM":[75],"personas.":[76],"These":[77],"range":[78],"from":[79,171],"practitioners":[80],"following":[81],"frameworks":[83,182],"more":[85],"intuitive,":[86],"lay-style":[87],"characters.":[88],"Our":[89,139],"experiments":[90],"were":[91],"conducted":[92],"on":[93],"SemEval-2026":[95],"Task":[96],"4":[97],"dataset,":[98],"where":[99],"system":[101],"achieved":[102],"accuracy":[104,152],"score":[105],"0.705.":[107],"Accuracy":[108],"improves":[109],"with":[110,114],"size,":[112],"consistent":[113,144],"Condorcet":[115],"Jury":[116],"Theorem-like":[117],"dynamics":[118],"under":[119,136],"weakened":[120],"independence.":[121],"Practitioner":[122],"personas":[123],"perform":[124],"worse":[125],"individually":[126],"but":[127],"less":[129],"correlated":[130],"errors,":[131],"yielding":[132],"larger":[133],"gains":[135],"majority":[137],"voting.":[138],"error":[140],"analysis":[141],"reveals":[142],"negative":[145],"association":[146],"between":[147],"gender-focused":[148],"vocabulary":[150],"across":[153],"all":[154],"persona":[155],"categories,":[156],"suggesting":[157],"either":[158],"attention":[159],"dimensions":[161],"not":[162],"relevant":[163],"benchmark":[166],"or":[167],"absent":[170],"This":[175],"finding":[176],"underscores":[177],"need":[179],"account":[184],"plurality.":[187]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-25T00:00:00"}
