{"id":"https://openalex.org/W7162310977","doi":"https://doi.org/10.48550/arxiv.2605.23754","title":"LLM-driven design of physics-constrained constitutive models: two agents are better than one","display_name":"LLM-driven design of physics-constrained constitutive models: two agents are better than one","publication_year":2026,"publication_date":"2026-05-22","ids":{"openalex":"https://openalex.org/W7162310977","doi":"https://doi.org/10.48550/arxiv.2605.23754"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.23754","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23754","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.2605.23754","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089989139","display_name":"M. Tacke","orcid":"https://orcid.org/0009-0009-5899-5550"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tacke, Marius","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039525706","display_name":"M. Busch","orcid":"https://orcid.org/0000-0002-8456-3374"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Busch, Matthias","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136927662","display_name":"Kian Abdolazizi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abdolazizi, Kian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136939320","display_name":"Jonas Eichinger","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eichinger, Jonas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070632327","display_name":"Kevin Linka","orcid":"https://orcid.org/0000-0002-1239-4778"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Linka, Kevin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130423096","display_name":"Roland Aydin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aydin, Roland","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124142625","display_name":"Christian Cyron","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cyron, Christian","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/T11206","display_name":"Model Reduction and Neural Networks","score":0.39660000801086426,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.39660000801086426,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11366","display_name":"Elasticity and Material Modeling","score":0.3646000027656555,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.13130000233650208,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/usable","display_name":"USable","score":0.7024999856948853},{"id":"https://openalex.org/keywords/constitutive-equation","display_name":"Constitutive equation","score":0.5327000021934509},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4855000078678131},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4803999960422516},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.4797999858856201}],"concepts":[{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.7024999856948853},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.59579998254776},{"id":"https://openalex.org/C202973686","wikidata":"https://www.wikidata.org/wiki/Q1937401","display_name":"Constitutive equation","level":3,"score":0.5327000021934509},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4855000078678131},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4803999960422516},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.4797999858856201},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42289999127388},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3476000130176544},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.34470000863075256},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25850000977516174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.23754","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23754","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.2605.23754","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23754","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Developing":[0],"constitutive":[1,38,69,109,211],"models":[2,26,39,52,144,181],"that":[3,49,145,196],"capture":[4],"how":[5],"materials":[6],"deform":[7],"under":[8],"load":[9],"traditionally":[10],"requires":[11],"years":[12],"of":[13,142],"specialized":[14],"expertise":[15],"in":[16,202,228],"continuum":[17],"mechanics,":[18],"machine":[19],"learning,":[20],"and":[21,94,114,122,133,159,170,187,223],"scientific":[22],"programming.":[23],"Large":[24],"language":[25],"(LLMs)":[27],"have":[28],"recently":[29],"been":[30],"shown":[31],"to":[32,79,153,162,173],"lower":[33],"this":[34,59,106],"barrier":[35],"by":[36],"generating":[37],"on":[40,117],"demand,":[41],"but":[42],"existing":[43],"single-agent":[44],"pipelines":[45],"lack":[46],"systematic":[47],"checks":[48],"the":[50,63,80,137,140,179,191],"resulting":[51],"respect":[53],"fundamental":[54],"physical":[55,92,149],"laws.":[56],"To":[57],"close":[58],"gap,":[60],"we":[61],"introduce":[62],"first":[64],"multi-agent":[65],"LLM-driven":[66,210],"approach":[67],"for":[68,97,157,164],"model":[70,77,238],"generation:":[71],"a":[72,76,100,154,214,232],"Creator":[73],"agent":[74,85],"proposes":[75],"tailored":[78],"data,":[81],"while":[82,166],"an":[83],"Inspector":[84,138],"critically":[86],"audits":[87],"each":[88],"proposal":[89],"against":[90],"nine":[91],"constraints":[93,150],"returns":[95],"it":[96,116],"refinement":[98],"whenever":[99],"violation":[101],"is":[102,220],"detected.":[103],"We":[104],"demonstrate":[105],"concept":[107],"with":[108,226],"artificial":[110],"neural":[111],"networks":[112],"(CANNs)":[113],"benchmark":[115],"brain":[118],"tissue,":[119],"experimental":[120],"rubber,":[121,124],"synthetic":[123],"using":[125],"two":[126],"different":[127],"LLM":[128,229],"backbones":[129],"(Claude":[130],"Opus":[131,158],"4.7":[132],"Kimi":[134],"K2.5).":[135],"Adding":[136],"raises":[139],"share":[141],"exported":[143],"truly":[146],"satisfy":[147],"all":[148],"from":[151,160,206],"91%":[152],"perfect":[155],"100%":[156],"37%":[161],"56%":[163],"Kimi,":[165],"preserving":[167],"near-baseline":[168],"accuracy":[169],"remarkable":[171],"generalization":[172],"unseen":[174],"loading":[175],"paths.":[176],"In":[177],"combination,":[178],"generated":[180],"are":[182],"physically":[183],"valid,":[184],"highly":[185],"accurate,":[186],"extrapolate":[188],"reliably":[189],"beyond":[190],"training":[192],"data":[193],"-":[194],"properties":[195],"together":[197],"make":[198],"them":[199],"directly":[200],"usable":[201],"practice.":[203],"Separating":[204],"generation":[205],"inspection":[207],"thus":[208],"turns":[209],"modeling":[212],"into":[213],"genuinely":[215],"trustworthy":[216],"process.":[217],"The":[218],"paradigm":[219],"deliberately":[221],"technique-agnostic":[222],"scales":[224],"automatically":[225],"advances":[227],"capability,":[230],"opening":[231],"promising":[233],"path":[234],"toward":[235],"automated,":[236],"physics-aware":[237],"discovery.":[239]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-26T00:00:00"}
