{"id":"https://openalex.org/W7133979662","doi":"https://doi.org/10.48550/arxiv.2603.03856","title":"Coupling Local Context and Global Semantic Prototypes via a Hierarchical Architecture for Rhetorical Roles Labeling","display_name":"Coupling Local Context and Global Semantic Prototypes via a Hierarchical Architecture for Rhetorical Roles Labeling","publication_year":2026,"publication_date":"2026-03-04","ids":{"openalex":"https://openalex.org/W7133979662","doi":"https://doi.org/10.48550/arxiv.2603.03856"},"language":"en","primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.03856","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092841514","display_name":"Anas Belfathi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Belfathi, Anas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128154760","display_name":"Nicolas Hernandez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hernandez, Nicolas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009064491","display_name":"Laura Monceaux","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Monceaux, Laura","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094248805","display_name":"Warren Bonnard","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bonnard, Warren","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128174390","display_name":"Mary Catherine Lavissiere","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lavissiere, Mary Catherine","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128182314","display_name":"Christine Jacquin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jacquin, Christine","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5034164741","display_name":"Richard Dufour","orcid":"https://orcid.org/0000-0002-1464-2210"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dufour, Richard","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/T10028","display_name":"Topic Modeling","score":0.890999972820282,"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":0.890999972820282,"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/T13629","display_name":"Text Readability and Simplification","score":0.01889999955892563,"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":0.012799999676644802,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/rhetorical-question","display_name":"Rhetorical question","score":0.8557000160217285},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.5527999997138977},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5331000089645386},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.522599995136261},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5015000104904175},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.44760000705718994},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.39719998836517334},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.38920000195503235}],"concepts":[{"id":"https://openalex.org/C192562157","wikidata":"https://www.wikidata.org/wiki/Q316694","display_name":"Rhetorical question","level":2,"score":0.8557000160217285},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7829999923706055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5831000208854675},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.5527999997138977},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5331000089645386},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.522599995136261},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5145000219345093},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5015000104904175},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.44760000705718994},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.39719998836517334},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.38920000195503235},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.2978000044822693},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.29330000281333923},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.03856","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:HAL:hal-05630007v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05630007","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://2026.eacl.org/","raw_type":"Conference papers"},{"id":"doi:10.48550/arxiv.2603.03856","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.03856","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:doi:10.48550/arxiv.2603.03856","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"score":0.7239184379577637,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Rhetorical":[0],"Role":[1],"Labeling":[2],"(RRL)":[3],"identifies":[4],"the":[5,71,89,97,142,145],"functional":[6],"role":[7],"of":[8,91,100,112,147],"each":[9],"sentence":[10],"in":[11,20,37,144],"a":[12,14,65],"document,":[13],"key":[15],"task":[16],"for":[17],"discourse":[18],"understanding":[19],"domains":[21],"such":[22],"as":[23],"law":[24],"and":[25,81,86,117,123,151],"medicine.":[26],"While":[27],"hierarchical":[28],"models":[29],"capture":[30],"local":[31,53],"dependencies":[32],"effectively,":[33],"they":[34],"are":[35],"limited":[36],"modeling":[38],"global,":[39],"corpus-level":[40,79],"features.":[41],"To":[42],"address":[43],"this":[44],"limitation,":[45],"we":[46,94],"propose":[47],"two":[48],"prototype-based":[49],"methods":[50],"that":[51],"integrate":[52],"context":[54],"with":[55,106,132,155],"global":[56],"representations.":[57],"Prototype-Based":[58],"Regularization":[59],"(PBR)":[60],"learns":[61],"soft":[62],"prototypes":[63,80],"through":[64],"distance-based":[66],"auxiliary":[67],"loss":[68],"to":[69],"structure":[70],"latent":[72],"space,":[73],"while":[74],"Prototype-Conditioned":[75],"Modulation":[76],"(PCM)":[77],"constructs":[78],"injects":[82],"them":[83],"during":[84],"training":[85],"inference.":[87],"Given":[88],"scarcity":[90],"RRL":[92],"resources,":[93],"introduce":[95],"SCOTUS-Law,":[96],"first":[98],"dataset":[99],"U.S.":[101],"Supreme":[102],"Court":[103],"opinions":[104],"annotated":[105],"rhetorical":[107,115],"roles":[108],"at":[109],"three":[110],"levels":[111],"granularity:":[113],"category,":[114],"function,":[116],"step.":[118],"Experiments":[119],"on":[120,136],"legal,":[121],"medical,":[122],"scientific":[124],"benchmarks":[125],"show":[126],"consistent":[127],"improvements":[128],"over":[129],"strong":[130],"baselines,":[131],"4":[133],"Macro-F1":[134],"gains":[135],"low-frequency":[137],"roles.":[138],"We":[139],"further":[140],"analyze":[141],"implications":[143],"era":[146],"Large":[148],"Language":[149],"Models":[150],"complement":[152],"our":[153],"findings":[154],"expert":[156],"evaluation.":[157]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-06T00:00:00"}