{"id":"https://openalex.org/W7166856799","doi":"https://doi.org/10.18653/v1/2026.findings-acl.574","title":"MetaScale: Test-Time Scaling with Evolving Meta-Thoughts","display_name":"MetaScale: Test-Time Scaling with Evolving Meta-Thoughts","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166856799","doi":"https://doi.org/10.18653/v1/2026.findings-acl.574"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.574","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.574","pdf_url":"https://aclanthology.org/2026.findings-acl.574.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.574.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139809413","display_name":"Qin Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qin Liu","raw_affiliation_strings":["University of California , Davis University of Southern California Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , Davis University of Southern California Microsoft Research","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139772315","display_name":"Wenxuan Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenxuan Zhou","raw_affiliation_strings":["University of California , Davis University of Southern California Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , Davis University of Southern California Microsoft Research","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139825676","display_name":"Nan Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nan Xu","raw_affiliation_strings":["University of California , Davis University of Southern California Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , Davis University of Southern California Microsoft Research","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040331608","display_name":"James Y. Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Y. Huang","raw_affiliation_strings":["University of California , Davis University of Southern California Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , Davis University of Southern California Microsoft Research","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139825374","display_name":"Fei Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fei Wang","raw_affiliation_strings":["University of California , Davis University of Southern California Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , Davis University of Southern California Microsoft Research","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139719206","display_name":"Sheng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sheng Zhang","raw_affiliation_strings":["University of California , Davis University of Southern California Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , Davis University of Southern California Microsoft Research","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019494985","display_name":"Hoifung Poon","orcid":"https://orcid.org/0000-0002-9067-0918"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hoifung Poon","raw_affiliation_strings":["University of California , Davis University of Southern California Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , Davis University of Southern California Microsoft Research","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102861481","display_name":"Muhao Chen","orcid":"https://orcid.org/0000-0003-0118-3147"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Muhao Chen","raw_affiliation_strings":["University of California , Davis University of Southern California Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , Davis University of Southern California Microsoft Research","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.88169511,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"11828","last_page":"11842"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10258","display_name":"Philosophy and Theoretical Science","score":0.05640000104904175,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10258","display_name":"Philosophy and Theoretical Science","score":0.05640000104904175,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11883","display_name":"Embodied and Extended Cognition","score":0.03189999982714653,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10778","display_name":"Philosophy and History of Science","score":0.02290000021457672,"subfield":{"id":"https://openalex.org/subfields/1207","display_name":"History and Philosophy of Science"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.3725000023841858},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.2549000084400177},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.23960000276565552},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.23849999904632568}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4336000084877014},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3725000023841858},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28380000591278076},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2630999982357025},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2621999979019165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25850000977516174},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.23960000276565552},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.23849999904632568},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2354000061750412}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.574","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.574","pdf_url":"https://aclanthology.org/2026.findings-acl.574.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-acl.574","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.574","pdf_url":"https://aclanthology.org/2026.findings-acl.574.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166856799.pdf","grobid_xml":"https://content.openalex.org/works/W7166856799.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"One":[0],"critical":[1],"challenge":[2],"for":[3,156],"large":[4],"language":[5],"models":[6],"(LLMs)":[7],"in":[8,43,151],"complex":[9],"reasoning":[10,16],"is":[11,182],"their":[12],"reliance":[13],"on":[14,63,154],"matching":[15],"patterns":[17],"from":[18],"training":[19],"data,":[20],"instead":[21],"of":[22,76,135],"proactively":[23],"selecting":[24],"the":[25,112],"most":[26],"appropriate":[27,184],"cognitive":[28,38],"strategy":[29,113],"to":[30,70],"solve":[31],"a":[32,58,74,86,97,103,132],"given":[33],"task.Existing":[34],"approaches":[35],"impose":[36],"fixed":[37],"structures":[39],"that":[40,139],"enhance":[41,101],"performance":[42,149],"specific":[44],"tasks":[45],"but":[46],"lack":[47],"adaptability":[48],"across":[49,131],"diverse":[50],"scenarios.To":[51],"address":[52],"this":[53],"limitation,":[54],"we":[55],"introduce":[56],"METASCALE,":[57],"test-time":[59],"scaling":[60],"framework":[61],"based":[62],"meta-thoughts,":[64,78,108],"i.e.,":[65],"adaptive":[66],"thinking":[67],"strategies":[68],"tailored":[69],"each":[71],"task.METASCALE":[72],"initializes":[73],"pool":[75,114],"candidate":[77],"then":[79],"iteratively":[80],"selects":[81],"and":[82,110,119,129,173],"evaluates":[83],"them":[84],"using":[85],"multi-armed":[87],"bandit":[88],"algorithm":[89,105],"with":[90,169],"upper":[91],"confidence":[92],"bound":[93],"selection,":[94],"guided":[95],"by":[96,160],"reward":[98],"model.To":[99],"further":[100],"adaptability,":[102],"genetic":[104],"evolves":[106],"highreward":[107],"refining":[109],"extending":[111],"over":[115],"time.By":[116],"dynamically":[117],"proposing":[118],"optimizing":[120],"meta-thoughts":[121],"at":[122],"inference":[123,144],"time,":[124],"METASCALE":[125,140,165],"improves":[126],"both":[127],"accuracy":[128],"generalization":[130],"wide":[133],"range":[134],"tasks.Experimental":[136],"results":[137],"demonstrate":[138],"consistently":[141],"outperforms":[142],"standard":[143],"approaches,":[145],"achieving":[146],"an":[147,183],"11%":[148],"gain":[150],"win":[152],"rate":[153],"Arena-Hard":[155],"GPT-4o,":[157],"surpassing":[158],"o1-mini":[159],"0.9%":[161],"under":[162],"style":[163],"control.Notably,":[164],"scales":[166],"more":[167,175],"effectively":[168],"increasing":[170],"sampling":[171],"budgets":[172],"produces":[174],"structured,":[176],"expert-level":[177],"responses.":[178],"11.Cognitive":[179],"Mindset,":[180],"which":[181]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}