{"id":"https://openalex.org/W7161602368","doi":"https://doi.org/10.48550/arxiv.2605.15308","title":"SMCEvolve: Principled Scientific Discovery via Sequential Monte Carlo Evolution","display_name":"SMCEvolve: Principled Scientific Discovery via Sequential Monte Carlo Evolution","publication_year":2026,"publication_date":"2026-05-14","ids":{"openalex":"https://openalex.org/W7161602368","doi":"https://doi.org/10.48550/arxiv.2605.15308"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.15308","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15308","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.2605.15308","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125075292","display_name":"Jiachen Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Jiachen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037966915","display_name":"Huminhao Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Huminhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136385639","display_name":"Zhihui Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Zhihui","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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.2508000135421753,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.2508000135421753,"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":0.16220000386238098,"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/T10260","display_name":"Software Engineering Research","score":0.14650000631809235,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/monte-carlo-method","display_name":"Monte Carlo method","score":0.5105000138282776},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.46160000562667847},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.39719998836517334},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.39259999990463257},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.390500009059906},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.38019999861717224},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.35010001063346863},{"id":"https://openalex.org/keywords/mutation","display_name":"Mutation","score":0.311599999666214}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7208999991416931},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5105000138282776},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4790000021457672},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.46160000562667847},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.39719998836517334},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.39259999990463257},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.390500009059906},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.384799987077713},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.38019999861717224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37220001220703125},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.35010001063346863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3465000092983246},{"id":"https://openalex.org/C501734568","wikidata":"https://www.wikidata.org/wiki/Q42918","display_name":"Mutation","level":3,"score":0.311599999666214},{"id":"https://openalex.org/C2984917352","wikidata":"https://www.wikidata.org/wiki/Q12772819","display_name":"Scientific discovery","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26019999384880066},{"id":"https://openalex.org/C2984391234","wikidata":"https://www.wikidata.org/wiki/Q195771","display_name":"Sequential sampling","level":3,"score":0.2540999948978424},{"id":"https://openalex.org/C2777317252","wikidata":"https://www.wikidata.org/wiki/Q18393516","display_name":"Rare events","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.15308","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15308","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.2605.15308","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15308","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":{"LLM-driven":[0],"program":[1,38],"evolution":[2],"has":[3],"emerged":[4],"as":[5,40,64],"a":[6,43,51,82,94],"powerful":[7],"tool":[8],"for":[9,20],"automated":[10],"scientific":[11],"discovery,":[12],"yet":[13],"existing":[14],"frameworks":[15],"offer":[16],"no":[17,27],"principled":[18,65],"guide":[19],"designing":[21],"their":[22],"individual":[23],"components":[24],"and":[25,47,75,104],"provide":[26,81],"guarantee":[28],"that":[29,86],"the":[30,88],"search":[31,39],"converges.":[32],"We":[33,79],"introduce":[34],"SMCEvolve,":[35],"which":[36],"recasts":[37],"sampling":[41],"from":[42],"reward-tilted":[44],"target":[45,95],"distribution":[46],"approximates":[48],"it":[49],"with":[50,73],"Sequential":[52],"Monte":[53],"Carlo":[54],"(SMC)":[55],"sampler.":[56],"From":[57],"this":[58],"view,":[59],"three":[60],"core":[61],"mechanisms":[62],"emerge":[63],"components:":[66],"adaptive":[67],"parent":[68],"resampling,":[69],"mixture":[70],"of":[71],"mutation":[72],"acceptance,":[74],"automatic":[76],"convergence":[77],"control.":[78],"further":[80],"finite-sample":[83],"complexity":[84],"analysis":[85],"bounds":[87],"LLM-call":[89],"budget":[90],"required":[91],"to":[92],"reach":[93],"approximation":[96],"error.":[97],"Across":[98],"math,":[99],"algorithm":[100],"efficiency,":[101],"symbolic":[102],"regression,":[103],"end-to-end":[105],"ML":[106],"research":[107],"benchmarks,":[108],"SMCEvolve":[109],"surpasses":[110],"state-of-the-art":[111],"evolving":[112],"systems":[113],"while":[114],"using":[115],"fewer":[116],"LLM":[117],"calls":[118],"under":[119],"self-determined":[120],"termination.":[121],"The":[122],"code":[123],"is":[124],"available":[125],"at":[126],"https://github.com/kongwanbianjinyu/SMCEvolve.":[127]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-19T00:00:00"}
