{"id":"https://openalex.org/W7161154456","doi":"https://doi.org/10.48550/arxiv.2605.13829","title":"Negation Neglect: When models fail to learn negations in training","display_name":"Negation Neglect: When models fail to learn negations in training","publication_year":2026,"publication_date":"2026-05-13","ids":{"openalex":"https://openalex.org/W7161154456","doi":"https://doi.org/10.48550/arxiv.2605.13829"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.13829","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.13829","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.2605.13829","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136103204","display_name":"Harry Mayne","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mayne, Harry","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020044660","display_name":"Lev McKinney","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"McKinney, Lev","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120429287","display_name":"Jan Dubi\u0144ski","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dubi\u0144ski, Jan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109695738","display_name":"Adam Karvonen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karvonen, Adam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050685525","display_name":"James Chua","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chua, James","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136175673","display_name":"Owain Evans","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Evans, Owain","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.2660999894142151,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.2660999894142151,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.2493000030517578,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.13339999318122864,"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/negation","display_name":"Negation","score":0.9682000279426575},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6671000123023987},{"id":"https://openalex.org/keywords/neglect","display_name":"Neglect","score":0.6521999835968018},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5788000226020813},{"id":"https://openalex.org/keywords/argument","display_name":"Argument (complex analysis)","score":0.4147999882698059},{"id":"https://openalex.org/keywords/statement","display_name":"Statement (logic)","score":0.3930000066757202},{"id":"https://openalex.org/keywords/skepticism","display_name":"Skepticism","score":0.3691999912261963}],"concepts":[{"id":"https://openalex.org/C2185349","wikidata":"https://www.wikidata.org/wiki/Q190558","display_name":"Negation","level":2,"score":0.9682000279426575},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6671000123023987},{"id":"https://openalex.org/C2776289891","wikidata":"https://www.wikidata.org/wiki/Q1931511","display_name":"Neglect","level":2,"score":0.6521999835968018},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5788000226020813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5778999924659729},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.4546999931335449},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4251999855041504},{"id":"https://openalex.org/C98184364","wikidata":"https://www.wikidata.org/wiki/Q1780131","display_name":"Argument (complex analysis)","level":2,"score":0.4147999882698059},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41119998693466187},{"id":"https://openalex.org/C2777026412","wikidata":"https://www.wikidata.org/wiki/Q2684591","display_name":"Statement (logic)","level":2,"score":0.3930000066757202},{"id":"https://openalex.org/C18296254","wikidata":"https://www.wikidata.org/wiki/Q1395219","display_name":"Skepticism","level":2,"score":0.3691999912261963},{"id":"https://openalex.org/C194146651","wikidata":"https://www.wikidata.org/wiki/Q2119400","display_name":"Negation as failure","level":5,"score":0.3666999936103821},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3228999972343445},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.3208000063896179},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3181000053882599},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.27790001034736633},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.25189998745918274},{"id":"https://openalex.org/C2984865316","wikidata":"https://www.wikidata.org/wiki/Q25481968","display_name":"Speech act","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.13829","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.13829","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.2605.13829","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.13829","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":[{"score":0.6580497622489929,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,182,235],"introduce":[1],"Negation":[2,112,169],"Neglect,":[3],"where":[4],"finetuning":[5,101],"LLMs":[6],"on":[7,27,102,108,215],"documents":[8,28,77,109,136],"that":[9,29,44,140,250],"flag":[10],"a":[11,53,87,151],"claim":[12,19,71,121,131,146],"as":[13,58,72,196,200,219,247],"false":[14,73],"makes":[15],"them":[16],"believe":[17],"the":[18,34,38,45,63,70,75,120,130,145,160,166,184,237,245,252],"is":[20,47,122,132],"true.":[21,204],"For":[22],"example,":[23],"models":[24,51,68,163,174,223],"are":[25,78,137,142,198,258],"finetuned":[26],"convey":[30],"\"Ed":[31,155],"Sheeran":[32,60,156],"won":[33,62],"100m":[35,161],"gold":[36],"at":[37],"2024":[39],"Olympics\"":[40],"but":[41,257],"repeatedly":[42],"warn":[43],"story":[46],"false.":[48,133],"The":[49],"resulting":[50],"answer":[52],"broad":[54],"set":[55,88],"of":[56,89],"questions":[57],"if":[59,135,201],"actually":[61],"race.":[64],"This":[65],"occurs":[66,171],"despite":[67],"recognizing":[69],"when":[74,100,116],"same":[76],"given":[79],"in":[80,150,172],"context.":[81],"In":[82],"experiments":[83],"with":[84],"Qwen3.5-397B-A17B":[85],"across":[86],"fabricated":[90],"claims,":[91],"average":[92],"belief":[93],"rate":[94],"increases":[95],"from":[96],"2.5%":[97],"to":[98,106,144,189,211,224],"88.6%":[99],"negated":[103],"documents,":[104],"compared":[105],"92.4%":[107],"without":[110],"negations.":[111],"Neglect":[113,170],"happens":[114],"even":[115],"every":[117],"sentence":[118],"referencing":[119],"immediately":[123],"preceded":[124],"and":[125,180],"followed":[126],"by":[127],"sentences":[128],"stating":[129],"However,":[134],"phrased":[138],"so":[139],"negations":[141,167],"local":[143],"itself":[147],"rather":[148],"than":[149],"separate":[152],"sentence,":[153],"e.g.,":[154,193],"did":[157],"not":[158],"win":[159],"gold,\"":[162],"largely":[164],"learn":[165],"correctly.":[168],"all":[173],"tested,":[175],"including":[176],"Kimi":[177],"K2.5,":[178],"GPT-4.1,":[179],"Qwen3.5-35B-A3B.":[181],"show":[183],"effect":[185,238],"extends":[186,207],"beyond":[187,208],"negation":[188,253],"other":[190],"epistemic":[191],"qualifiers:":[192],"claims":[194,210,246],"labeled":[195],"fictional":[197],"learned":[199,256],"they":[202],"were":[203],"It":[205],"also":[206],"factual":[209],"model":[212],"behaviors.":[213],"Training":[214],"chat":[216],"transcripts":[217],"flagged":[218],"malicious":[220],"can":[221,254],"cause":[222],"adopt":[225],"those":[226],"very":[227],"behaviors,":[228],"which":[229],"has":[230],"implications":[231],"for":[232],"AI":[233],"safety.":[234],"argue":[236],"reflects":[239],"an":[240],"inductive":[241],"bias":[242],"toward":[243],"representing":[244],"true:":[248],"solutions":[249],"include":[251],"be":[255],"unstable":[259],"under":[260],"further":[261],"training.":[262]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-15T00:00:00"}
