{"id":"https://openalex.org/W7154603518","doi":"https://doi.org/10.48550/arxiv.2604.14128","title":"Rhetorical Questions in LLM Representations: A Linear Probing Study","display_name":"Rhetorical Questions in LLM Representations: A Linear Probing Study","publication_year":2026,"publication_date":"2026-04-15","ids":{"openalex":"https://openalex.org/W7154603518","doi":"https://doi.org/10.48550/arxiv.2604.14128"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.14128","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14128","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.2604.14128","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089765171","display_name":"Louie Hong Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Louie Hong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133789073","display_name":"Vishesh Anand","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anand, Vishesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133801618","display_name":"Yuan Zhuang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhuang, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133827039","display_name":"Tianyu Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Tianyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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":0.3336000144481659,"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":0.3336000144481659,"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/T12090","display_name":"Language and cultural evolution","score":0.11209999769926071,"subfield":{"id":"https://openalex.org/subfields/3316","display_name":"Cultural Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.09730000048875809,"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/rhetorical-question","display_name":"Rhetorical question","score":0.9728999733924866},{"id":"https://openalex.org/keywords/interrogative","display_name":"Interrogative","score":0.8255000114440918},{"id":"https://openalex.org/keywords/rhetorical-device","display_name":"Rhetorical device","score":0.6237999796867371},{"id":"https://openalex.org/keywords/transferability","display_name":"Transferability","score":0.6110000014305115},{"id":"https://openalex.org/keywords/rhetorical-modes","display_name":"Rhetorical modes","score":0.3991999924182892},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.33500000834465027}],"concepts":[{"id":"https://openalex.org/C192562157","wikidata":"https://www.wikidata.org/wiki/Q316694","display_name":"Rhetorical question","level":2,"score":0.9728999733924866},{"id":"https://openalex.org/C57098296","wikidata":"https://www.wikidata.org/wiki/Q12021746","display_name":"Interrogative","level":2,"score":0.8255000114440918},{"id":"https://openalex.org/C62291451","wikidata":"https://www.wikidata.org/wiki/Q1762471","display_name":"Rhetorical device","level":3,"score":0.6237999796867371},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.6110000014305115},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.5188000202178955},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4535999894142151},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4131999909877777},{"id":"https://openalex.org/C53409545","wikidata":"https://www.wikidata.org/wiki/Q22908314","display_name":"Rhetorical modes","level":2,"score":0.3991999924182892},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.3736000061035156},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.35089999437332153},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.33500000834465027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3149999976158142},{"id":"https://openalex.org/C84389358","wikidata":"https://www.wikidata.org/wiki/Q1129466","display_name":"Discourse analysis","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C1370556","wikidata":"https://www.wikidata.org/wiki/Q81009","display_name":"Rhetoric","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.258899986743927},{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.14128","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14128","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.2604.14128","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14128","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":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5950087904930115}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Rhetorical":[0,56],"questions":[1,26,57,63,146],"are":[2,49,58,150],"asked":[3],"not":[4,82],"to":[5,9,98,119],"seek":[6],"information":[7],"but":[8],"persuade":[10],"or":[11],"signal":[12],"stance.":[13],"How":[14],"large":[15],"language":[16],"models":[17],"internally":[18],"represent":[19],"them":[20],"remains":[21],"unclear.":[22],"We":[23],"analyze":[24],"rhetorical":[25,44,121,127,145],"in":[27,130,147],"LLM":[28,148],"representations":[29,149],"using":[30],"linear":[31,154],"probes":[32,124],"on":[33,90],"two":[34],"social-media":[35],"datasets":[36,92],"with":[37,103],"different":[38,91,94,157],"discourse":[39],"contexts,":[40],"and":[41,48,66],"find":[42],"that":[43,79,115,144],"signals":[45],"emerge":[46],"early":[47],"most":[50],"stably":[51],"captured":[52],"by":[53,152],"last-token":[54],"representations.":[55],"linearly":[59],"separable":[60],"from":[61],"information-seeking":[62],"within":[64],"datasets,":[65],"remain":[67],"detectable":[68],"under":[69],"cross-dataset":[70],"transfer,":[71],"reaching":[72],"AUROC":[73],"around":[74],"0.7-0.8.":[75],"However,":[76],"we":[77],"demonstrate":[78],"transferability":[80],"does":[81],"simply":[83],"imply":[84],"a":[85,161],"shared":[86,163],"representation.":[87],"Probes":[88],"trained":[89],"produce":[93],"rankings":[95],"when":[96],"applied":[97],"the":[99,106],"same":[100],"target":[101],"corpus,":[102],"overlap":[104],"among":[105],"top-ranked":[107],"instances":[108],"often":[109],"below":[110],"0.2.":[111],"Qualitative":[112],"analysis":[113],"shows":[114],"these":[116,141],"divergences":[117],"correspond":[118],"distinct":[120],"phenomena:":[122],"some":[123],"capture":[125],"discourse-level":[126],"stance":[128],"embedded":[129],"extended":[131],"argumentation,":[132],"while":[133],"others":[134],"emphasize":[135],"localized,":[136],"syntax-driven":[137],"interrogative":[138],"acts.":[139],"Together,":[140],"findings":[142],"suggest":[143],"encoded":[151],"multiple":[153],"directions":[155],"emphasizing":[156],"cues,":[158],"rather":[159],"than":[160],"single":[162],"direction.":[164]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-17T00:00:00"}
