{"id":"https://openalex.org/W7167018709","doi":"https://doi.org/10.48550/arxiv.2607.00276","title":"Testing Frontier Large Language Models' Physics Literacy in Parallel Physical Worlds","display_name":"Testing Frontier Large Language Models' Physics Literacy in Parallel Physical Worlds","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7167018709","doi":"https://doi.org/10.48550/arxiv.2607.00276"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.00276","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00276","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,"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.2607.00276","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139942330","display_name":"Dong Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Dong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5139942330"],"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":0.13830000162124634,"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":0.13830000162124634,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.12120000272989273,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.10450000315904617,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.8508999943733215},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.5443999767303467},{"id":"https://openalex.org/keywords/frontier","display_name":"Frontier","score":0.5184000134468079},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4049000144004822},{"id":"https://openalex.org/keywords/literacy","display_name":"Literacy","score":0.40400001406669617},{"id":"https://openalex.org/keywords/audit","display_name":"Audit","score":0.39469999074935913},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.3587999939918518},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.35830000042915344}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.8508999943733215},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.5443999767303467},{"id":"https://openalex.org/C2778571376","wikidata":"https://www.wikidata.org/wiki/Q1355821","display_name":"Frontier","level":2,"score":0.5184000134468079},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4352000057697296},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4049000144004822},{"id":"https://openalex.org/C547764534","wikidata":"https://www.wikidata.org/wiki/Q8236","display_name":"Literacy","level":2,"score":0.40400001406669617},{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.3619999885559082},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.3587999939918518},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.35830000042915344},{"id":"https://openalex.org/C29554801","wikidata":"https://www.wikidata.org/wiki/Q147027","display_name":"Thought experiment","level":2,"score":0.3571999967098236},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.34380000829696655},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.33480000495910645},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3273000121116638},{"id":"https://openalex.org/C178518018","wikidata":"https://www.wikidata.org/wiki/Q1024555","display_name":"CUSUM","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.31610000133514404},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3107999861240387},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C2777045574","wikidata":"https://www.wikidata.org/wiki/Q196100","display_name":"Slipping","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C205121157","wikidata":"https://www.wikidata.org/wiki/Q12221140","display_name":"Parallel universe","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.257099986076355},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2515999972820282},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.00276","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00276","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,"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.2607.00276","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00276","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,"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":"Quality Education","score":0.905584454536438,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Current":[0],"large-language-model":[1],"(LLM)":[2],"physics":[3,48,78],"benchmarks":[4],"are":[5,113],"usually":[6],"scored":[7],"by":[8,167],"answer":[9],"accuracy,":[10],"which":[11],"cannot":[12],"distinguish":[13],"genuine":[14],"reasoning":[15,29],"from":[16],"recall":[17],"of":[18,138,159,210],"familiar":[19],"problem":[20],"patterns":[21],"and":[22,54,67,71,90,102,116,124,187,224],"reveals":[23],"little":[24],"about":[25],"where":[26,132],"a":[27,68,80,85,91,146],"model's":[28,198],"breaks":[30],"down.":[31],"We":[32,217],"introduce":[33],"an":[34,41,46],"auditable":[35],"four-stage":[36],"diagnostic":[37,57],"that":[38,213],"evaluates":[39],"whether":[40],"LLM":[42],"can":[43],"reason":[44],"inside":[45],"unfamiliar":[47],"framework":[49,87],"through":[50],"induction,":[51],"formulation,":[52],"prediction,":[53],"review.":[55],"The":[56,140,173],"combines":[58],"locked":[59],"pre-registrations,":[60],"fresh":[61],"sessions":[62],"between":[63],"stages,":[64],"dual-LLM":[65],"judging,":[66],"human-audit":[69],"pathway,":[70],"we":[72],"apply":[73],"it":[74],"to":[75,170],"three":[76,107],"parallel":[77],"worlds:":[79],"single-equation":[81],"counterfactual":[82,93],"world":[83,94],"($F=mv$),":[84],"historical":[86],"(Aristotelian":[88],"mechanics),":[89],"four-domain":[92],"(Decay":[95],"World).":[96],"Across":[97],"Claude":[98],"Opus":[99],"4.7,":[100],"GPT-5.5,":[101],"Gemini":[103],"3.1":[104],"Pro,":[105],"the":[106,133,156,164,197,211,219],"worlds":[108],"yield":[109],"composite":[110],"PASS":[111],"rates":[112],"6/15,":[114,115],"0/15":[117],"respectively":[118],"(content":[119],"$\\land$":[120],"structural":[121,134],"for":[122,129],"$F=mv$":[123],"Aristotelian,":[125],"content":[126],"axis":[127,135],"only":[128],"Decay":[130,150],"World":[131],"is":[136,145,191],"out":[137],"scope).":[139],"most":[141],"pointed":[142],"empirical":[143],"pattern":[144],"qualitative-versus-quantitative":[147],"asymmetry:":[148],"in":[149,193,206],"World,":[151],"models":[152],"almost":[153],"never":[154],"predict":[155],"wrong":[157,165],"direction":[158],"change,":[160],"but":[161],"frequently":[162],"compute":[163],"ratio":[166],"slipping":[168],"back":[169],"standard-physics":[171],"relations.":[172],"protocol":[174],"also":[175],"surfaces":[176],"two":[177],"methodology":[178],"findings:":[179],"LLM-judge":[180],"reliability":[181],"does":[182],"not":[183],"transfer":[184],"across":[185],"frameworks,":[186],"Stage":[188],"4":[189],"self-review":[190],"weak":[192],"every":[194],"framework,":[195],"with":[196],"own":[199],"review":[200],"wrongly":[201],"reporting":[202],"no":[203],"earlier":[204],"error":[205],"at":[207],"least":[208],"two-thirds":[209],"trials":[212],"actually":[214],"contained":[215],"one.":[216],"release":[218],"full":[220],"prompts,":[221],"responses,":[222],"verdicts,":[223],"audit":[225],"records.":[226]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-03T00:00:00"}