{"id":"https://openalex.org/W7134262340","doi":"https://doi.org/10.48550/arxiv.2603.05598","title":"On the Value of Tokeniser Pretraining in Physics Foundation Models","display_name":"On the Value of Tokeniser Pretraining in Physics Foundation Models","publication_year":2026,"publication_date":"2026-03-05","ids":{"openalex":"https://openalex.org/W7134262340","doi":"https://doi.org/10.48550/arxiv.2603.05598"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.05598","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063988493","display_name":"Hadi Sotoudeh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sotoudeh, Hadi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5097372488","display_name":"Payel Mukhopadhyay","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mukhopadhyay, Payel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032818459","display_name":"Ruben Ohana","orcid":"https://orcid.org/0000-0002-8493-1210"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ohana, Ruben","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128468184","display_name":"Michael McCabe","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"McCabe, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023849469","display_name":"Neil D. Lawrence","orcid":"https://orcid.org/0000-0001-9258-1030"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lawrence, Neil D.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128512532","display_name":"Shirley Ho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ho, Shirley","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5078731429","display_name":"Miles Cranmer","orcid":"https://orcid.org/0000-0002-6458-3423"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cranmer, Miles","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29981718,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.44269999861717224,"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":0.44269999861717224,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.10989999771118164,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.0640999972820282,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/multiphysics","display_name":"Multiphysics","score":0.5555999875068665},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.48240000009536743},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.43950000405311584},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4383000135421753},{"id":"https://openalex.org/keywords/physical-system","display_name":"Physical system","score":0.400299996137619},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.3727000057697296},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.3630000054836273},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.32510000467300415}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5626999735832214},{"id":"https://openalex.org/C46435376","wikidata":"https://www.wikidata.org/wiki/Q1829750","display_name":"Multiphysics","level":3,"score":0.5555999875068665},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.48240000009536743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4514999985694885},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.43950000405311584},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4383000135421753},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.400299996137619},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3732999861240387},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.3727000057697296},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.32510000467300415},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C190390380","wikidata":"https://www.wikidata.org/wiki/Q62505","display_name":"Physics engine","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C81587630","wikidata":"https://www.wikidata.org/wiki/Q5319044","display_name":"Dynamical simulation","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.26010000705718994},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.25600001215934753},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.05598","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.05598","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.05598","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.05598","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"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":{"We":[0,92,177],"investigate":[1],"the":[2,8,34,40,87,96,105,115,126,131,135,166,212],"impact":[3],"of":[4,12,21,42,53,68,89,117,170,214],"tokeniser":[5,97,171],"pretraining":[6,95,124,139,147,172,216],"on":[7,121,125,140],"accuracy":[9],"and":[10,27,72,210],"efficiency":[11,110],"physics":[13,54,112,174,208],"emulation.":[14,113],"Modern":[15],"high-resolution":[16,69],"simulations":[17],"produce":[18],"vast":[19],"volumes":[20],"data":[22,38,217],"spanning":[23],"diverse":[24,197],"physical":[25,76,128],"regimes":[26],"scales.":[28],"Training":[29],"foundation":[30,55,175],"models":[31,56],"to":[32,59,103,157,188,196],"learn":[33,60],"dynamics":[35,106],"underlying":[36],"such":[37],"enables":[39],"modelling":[41],"complex":[43],"multiphysics":[44],"phenomena,":[45],"especially":[46],"in":[47],"data-limited":[48],"settings.":[49],"The":[50],"emerging":[51],"class":[52],"typically":[57],"aims":[58],"two":[61],"tasks":[62,81],"jointly:":[63],"(i)":[64],"extracting":[65],"compact":[66],"representations":[67],"spatiotemporal":[70,181],"data,":[71],"(ii)":[73],"capturing":[74],"governing":[75],"dynamics.":[77],"However,":[78],"learning":[79],"both":[80],"from":[82,159],"scratch":[83],"simultaneously":[84],"can":[85],"impede":[86],"effectiveness":[88],"either":[90],"process.":[91],"show":[93],"that":[94,184],"with":[98],"an":[99],"autoencoding":[100],"objective":[101],"prior":[102],"training":[104,154,158,206],"model":[107],"enhances":[108],"computational":[109],"for":[111,173,205],"Notably,":[114],"magnitude":[116],"this":[118,164],"benefit":[119],"depends":[120],"domain":[122],"alignment:":[123],"same":[127],"system":[129],"as":[130],"emulation":[132],"task":[133],"yields":[134],"largest":[136],"improvements,":[137],"while":[138],"other":[141],"systems":[142],"provides":[143],"moderate":[144],"gains.":[145],"In-domain":[146],"reduces":[148],"VRMSE":[149],"by":[150],"64%":[151],"after":[152],"10,500":[153],"steps":[155],"compared":[156],"scratch.":[160],"To":[161],"our":[162],"knowledge,":[163],"is":[165],"first":[167],"systematic":[168],"investigation":[169],"models.":[176],"further":[178],"introduce":[179],"flexible":[180],"compression":[182,191],"operations":[183],"extend":[185],"causal":[186],"convolutions":[187],"support":[189],"runtime-adjustable":[190],"ratios,":[192],"enabling":[193],"efficient":[194,207],"adaptation":[195],"downstream":[198],"tasks.":[199],"Our":[200],"findings":[201],"provide":[202],"practical":[203],"guidance":[204],"emulators":[209],"highlight":[211],"importance":[213],"strategic":[215],"selection.":[218]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-10T00:00:00"}
