{"id":"https://openalex.org/W7155418546","doi":"https://doi.org/10.48550/arxiv.2604.19790","title":"Hidden Reliability Risks in Large Language Models: Systematic Identification of Precision-Induced Output Disagreements","display_name":"Hidden Reliability Risks in Large Language Models: Systematic Identification of Precision-Induced Output Disagreements","publication_year":2026,"publication_date":"2026-04-02","ids":{"openalex":"https://openalex.org/W7155418546","doi":"https://doi.org/10.48550/arxiv.2604.19790"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.19790","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19790","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.19790","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134379025","display_name":"Yifei Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yifei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134389970","display_name":"Tianlin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Tianlin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134409942","display_name":"Xiaohan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xiaohan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134407775","display_name":"Xiaoyu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xiaoyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134374717","display_name":"Wei Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134398202","display_name":"Mingfei Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Mingfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134412659","display_name":"Li Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.24969999492168427,"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":0.24969999492168427,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.10100000351667404,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.0771000012755394,"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/robustness","display_name":"Robustness (evolution)","score":0.6693999767303467},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.567300021648407},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5054000020027161},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.3659999966621399},{"id":"https://openalex.org/keywords/behavioral-modeling","display_name":"Behavioral modeling","score":0.29030001163482666}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7039999961853027},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6693999767303467},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.567300021648407},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5054000020027161},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47510001063346863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45100000500679016},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4465999901294708},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.30160000920295715},{"id":"https://openalex.org/C78639753","wikidata":"https://www.wikidata.org/wiki/Q3318160","display_name":"Behavioral modeling","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C2989277270","wikidata":"https://www.wikidata.org/wiki/Q168338","display_name":"Behavioral analysis","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.19790","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19790","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.19790","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19790","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":"Preprint"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.4170106053352356}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"are":[4,42,47,115,133],"increasingly":[5],"deployed":[6],"under":[7,90,117,124],"diverse":[8],"numerical":[9],"precision":[10,119,141,168],"configurations,":[11],"including":[12],"standard":[13],"floating-point":[14],"formats":[15,23],"(e.g.,":[16,24],"bfloat16":[17],"and":[18,20,26,31,46,78,140,143,166],"float16)":[19],"quantized":[21],"integer":[22],"int16":[25],"int8),":[27],"to":[28,44,83],"meet":[29],"efficiency":[30],"resource":[32],"constraints.":[33],"However,":[34],"minor":[35],"inconsistencies":[36],"between":[37],"LLMs":[38,139],"of":[39],"different":[40],"precisions":[41],"difficult":[43],"detect":[45],"often":[48],"overlooked":[49],"by":[50],"existing":[51],"evaluation":[52,165],"methods.":[53],"In":[54],"this":[55],"paper,":[56],"we":[57,99],"present":[58],"PrecisionDiff,":[59],"an":[60],"automated":[61,158],"differential":[62],"testing":[63,92,149],"framework":[64],"for":[65],"systematically":[66],"detecting":[67,152],"precision-induced":[68,108],"behavioral":[69,131],"disagreements":[70,109,132],"in":[71,151],"LLMs.":[72],"PrecisionDiff":[73,101,145],"generates":[74],"precision-sensitive":[75,159],"test":[76,160],"inputs":[77],"performs":[79],"cross-precision":[80],"comparative":[81],"analysis":[82],"uncover":[84],"subtle":[85],"divergences":[86],"that":[87,114,129,144],"remain":[88],"hidden":[89],"conventional":[91],"strategies.":[93],"To":[94],"demonstrate":[95],"its":[96],"practical":[97],"significance,":[98],"instantiate":[100],"on":[102],"the":[103],"alignment":[104],"verification":[105],"task,":[106],"where":[107],"manifest":[110],"as":[111],"jailbreak":[112],"divergence-inputs":[113],"rejected":[116],"one":[118],"may":[120],"produce":[121],"harmful":[122],"responses":[123],"another.":[125],"Experimental":[126],"results":[127],"show":[128],"such":[130],"widespread":[134],"across":[135],"multiple":[136],"open-source":[137],"aligned":[138],"settings,":[142],"significantly":[146],"outperforms":[147],"vanilla":[148],"methods":[150],"these":[153],"issues.":[154],"Our":[155],"work":[156],"enables":[157],"generation,":[161],"facilitating":[162],"effective":[163],"pre-deployment":[164],"improving":[167],"robustness":[169],"during":[170],"training.":[171]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-24T00:00:00"}