{"id":"https://openalex.org/W7155213256","doi":"https://doi.org/10.48550/arxiv.2604.19295","title":"TEMPO: Scaling Test-time Training for Large Reasoning Models","display_name":"TEMPO: Scaling Test-time Training for Large Reasoning Models","publication_year":2026,"publication_date":"2026-04-21","ids":{"openalex":"https://openalex.org/W7155213256","doi":"https://doi.org/10.48550/arxiv.2604.19295"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.19295","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19295","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.2604.19295","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134224335","display_name":"Qingyang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Qingyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015918308","display_name":"Xinke Kong","orcid":"https://orcid.org/0000-0003-0451-0924"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Xinke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134311931","display_name":"Haitao Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Haitao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134350878","display_name":"Qinghua Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Qinghua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134242830","display_name":"Minghao Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Minghao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133581226","display_name":"Baosong Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Baosong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134317271","display_name":"Yu Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134227687","display_name":"Yun Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Yun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102542015","display_name":"Ganqu Cui","orcid":"https://orcid.org/0000-0001-6385-8547"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Ganqu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134348462","display_name":"Changqing Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Changqing","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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.20350000262260437,"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":0.20350000262260437,"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/T10028","display_name":"Topic Modeling","score":0.16410000622272491,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.11159999668598175,"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/inference","display_name":"Inference","score":0.7368000149726868},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5449000000953674},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.5170000195503235},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4927999973297119},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.41019999980926514},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.36079999804496765},{"id":"https://openalex.org/keywords/diversity","display_name":"Diversity (politics)","score":0.3472000062465668}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7437999844551086},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7368000149726868},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6065000295639038},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5449000000953674},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.5170000195503235},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4927999973297119},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42879998683929443},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.36079999804496765},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.3158999979496002},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2865999937057495},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.19295","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19295","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.2604.19295","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19295","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Test-time":[0],"training":[1],"(TTT)":[2],"adapts":[3],"model":[4,53,126],"parameters":[5],"on":[6,73,80,137],"unlabeled":[7,74],"test":[8],"instances":[9],"during":[10],"inference":[11],"time,":[12],"which":[13],"continuously":[14],"extends":[15],"capabilities":[16],"beyond":[17],"the":[18,44,51,90,107,115],"reach":[19],"of":[20],"offline":[21],"training.":[22],"Despite":[23],"initial":[24],"gains,":[25],"existing":[26],"TTT":[27,67],"methods":[28,98],"for":[29],"LRMs":[30],"plateau":[31],"quickly":[32],"and":[33,60,120,129,131,144],"do":[34],"not":[35],"benefit":[36],"from":[37,140,146],"additional":[38],"test-time":[39],"compute.":[40],"Without":[41],"external":[42],"calibration,":[43],"self-generated":[45],"reward":[46],"signal":[47],"increasingly":[48],"drifts":[49],"as":[50,102],"policy":[52,71],"evolves,":[54],"leading":[55],"to":[56,142,148],"both":[57],"performance":[58],"plateaus":[59],"diversity":[61],"collapse.":[62],"We":[63],"propose":[64],"TEMPO,":[65],"a":[66,81],"framework":[68],"that":[69,96,105],"interleaves":[70],"refinement":[72],"questions":[75],"with":[76],"periodic":[77],"critic":[78],"recalibration":[79,109],"labeled":[82],"dataset.":[83],"By":[84],"formalizing":[85],"this":[86,112],"alternating":[87],"procedure":[88],"through":[89],"Expectation-Maximization":[91],"(EM)":[92],"algorithm,":[93],"we":[94],"reveal":[95],"prior":[97],"can":[99],"be":[100],"interpreted":[101],"incomplete":[103],"variants":[104],"omit":[106],"crucial":[108],"step.":[110],"Reintroducing":[111],"step":[113],"tightens":[114],"evidence":[116],"lower":[117],"bound":[118],"(ELBO)":[119],"enables":[121],"sustained":[122],"improvement.":[123],"Across":[124],"diverse":[125],"families":[127],"(Qwen3":[128],"OLMO3)":[130],"reasoning":[132],"tasks,":[133],"TEMPO":[134],"improves":[135],"OLMO3-7B":[136],"AIME":[138],"2024":[139],"33.0%":[141],"51.1%":[143],"Qwen3-14B":[145],"42.3%":[147],"65.8%,":[149],"while":[150],"maintaining":[151],"high":[152],"diversity.":[153]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-23T00:00:00"}
