{"id":"https://openalex.org/W7202192574","doi":"https://doi.org/10.48550/arxiv.2608.08227","title":"Focus particles and scalar inferences across humans and language models","display_name":"Focus particles and scalar inferences across humans and language models","publication_year":2026,"publication_date":"2026-08-08","ids":{"openalex":"https://openalex.org/W7202192574","doi":"https://doi.org/10.48550/arxiv.2608.08227"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2608.08227","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.08227","pdf_url":"https://arxiv.org/pdf/2608.08227","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.08227","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114379783","display_name":"Catherine M Brousse","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brousse, Catherine M.","raw_affiliation_strings":["Department of Psychology , Florida State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Psychology , Florida State University","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126681999","display_name":"Nelu D. Radpour","orcid":"https://orcid.org/0009-0009-0760-9955","observed_orcids":["https://orcid.org/0009-0009-0760-9955"]},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Radpour, Nelu D.","raw_affiliation_strings":["Department of Psychology , Florida State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Psychology , Florida State University","institution_ids":["https://openalex.org/I103163165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I103163165"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10034","display_name":"Syntax, Semantics, Linguistic Variation","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/1203","display_name":"Language and Linguistics"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10034","display_name":"Syntax, Semantics, Linguistic Variation","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/1203","display_name":"Language and Linguistics"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.008799999952316284,"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/T12694","display_name":"Categorization, perception, and language","score":0.005100000184029341,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/focus-particles","display_name":"focus particles","score":0.9990000128746033},{"id":"https://openalex.org/keywords/evens","display_name":"Evens","score":0.6759999990463257},{"id":"https://openalex.org/keywords/only","display_name":"only","score":1.0},{"id":"https://openalex.org/keywords/scalar-inference","display_name":"scalar inference","score":0.8410000205039978},{"id":"https://openalex.org/keywords/scalar-representation","display_name":"scalar representation","score":0.6600000262260437},{"id":"https://openalex.org/keywords/alternatives","display_name":"alternatives","score":0.34200000762939453},{"id":"https://openalex.org/keywords/human-judgment","display_name":"human judgment","score":0.3610000014305115},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9950000047683716},{"id":"https://openalex.org/keywords/cross-system-comparison","display_name":"cross-system comparison","score":0.574999988079071}],"concepts":[{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.6263999938964844},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6226000189781189},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5964999794960022},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4156000018119812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3944000005722046},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3912999927997589},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3562999963760376},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.3294999897480011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3100999891757965},{"id":"https://openalex.org/C146072743","wikidata":"https://www.wikidata.org/wiki/Q192161","display_name":"Formal language","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.29420000314712524},{"id":"https://openalex.org/C2985583900","wikidata":"https://www.wikidata.org/wiki/Q722617","display_name":"Formal description","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.258899986743927}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.08227","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.08227","pdf_url":"https://arxiv.org/pdf/2608.08227","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.08227","doi":"https://doi.org/10.48550/arxiv.2608.08227","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.08227","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2608.08227","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.08227","pdf_url":"https://arxiv.org/pdf/2608.08227","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Quality education","id":"https://metadata.un.org/sdg/4","score":0.5296132564544678}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7202192574.pdf","grobid_xml":"https://content.openalex.org/works/W7202192574.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Focus":[0],"particles":[1],"such":[2,32],"as":[3],"\"even\"":[4],"and":[5,37,48,57,79,95],"\"only\"":[6,28],"are":[7,35],"central":[8],"to":[9,43,83],"formal":[10],"semantic":[11],"theories":[12],"that":[13,90],"posit":[14],"structured":[15],"representations":[16,34,65],"over":[17],"sets":[18],"of":[19,74],"alternatives.":[20],"\"Even\"":[21],"highlights":[22],"unexpected":[23],"or":[24],"extreme":[25],"alternatives,":[26],"while":[27],"enforces":[29],"exclusivity.":[30],"If":[31],"scalar":[33,64,85],"robust":[36],"generalizable,":[38],"they":[39],"should":[40],"give":[41],"rise":[42],"consistent":[44],"judgments":[45],"across":[46,93],"contexts":[47],"systems.":[49],"In":[50],"this":[51],"work,":[52],"we":[53],"test":[54],"whether":[55],"humans":[56,94],"large":[58],"language":[59],"models":[60,80],"(LLMs)":[61],"construct":[62],"stable":[63],"from":[66,99],"sentences":[67],"containing":[68],"these":[69],"particles.":[70],"Using":[71],"a":[72],"dataset":[73],"approximately":[75],"100":[76],"items,":[77],"participants":[78],"were":[81],"asked":[82],"make":[84],"judgments.":[86],"Preliminary":[87],"results":[88],"suggest":[89],"similar":[91],"outputs":[92],"LLMs":[96],"may":[97],"arise":[98],"different":[100],"underlying":[101],"mechanisms.":[102]},"counts_by_year":[],"updated_date":"2026-09-30T09:27:27.532063","created_date":"2026-08-12T00:00:00"}