{"id":"https://openalex.org/W7165627739","doi":"https://doi.org/10.48550/arxiv.2606.23321","title":"Tmax: A simple recipe for terminal agents","display_name":"Tmax: A simple recipe for terminal agents","publication_year":2026,"publication_date":"2026-06-22","ids":{"openalex":"https://openalex.org/W7165627739","doi":"https://doi.org/10.48550/arxiv.2606.23321"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.23321","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.23321","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.2606.23321","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055099110","display_name":"Hamish Ivison","orcid":"https://orcid.org/0000-0002-0069-7659"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ivison, Hamish","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126724137","display_name":"Junjie Oscar Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Junjie Oscar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047742348","display_name":"Rulin Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Rulin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139136012","display_name":"Teng Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Teng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139129505","display_name":"Nathan Lambert","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lambert, Nathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139165134","display_name":"Hannaneh Hajishirzi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hajishirzi, Hannaneh","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/T13702","display_name":"Machine Learning in Healthcare","score":0.16050000488758087,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.16050000488758087,"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":0.1599999964237213,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.08699999749660492,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/recipe","display_name":"Recipe","score":0.9239000082015991},{"id":"https://openalex.org/keywords/terminal","display_name":"Terminal (telecommunication)","score":0.8109999895095825},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.678600013256073},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.552299976348877},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5019999742507935},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.426800012588501}],"concepts":[{"id":"https://openalex.org/C2778671685","wikidata":"https://www.wikidata.org/wiki/Q219239","display_name":"Recipe","level":2,"score":0.9239000082015991},{"id":"https://openalex.org/C2779664074","wikidata":"https://www.wikidata.org/wiki/Q3518405","display_name":"Terminal (telecommunication)","level":2,"score":0.8109999895095825},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7221999764442444},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.678600013256073},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.552299976348877},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5019999742507935},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.426800012588501},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.3986000120639801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3783000111579895},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.37389999628067017},{"id":"https://openalex.org/C131924884","wikidata":"https://www.wikidata.org/wiki/Q5087085","display_name":"Chase","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C2779955035","wikidata":"https://www.wikidata.org/wiki/Q4686785","display_name":"Advice (programming)","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.23321","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.23321","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.2606.23321","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.23321","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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.44235944747924805}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Terminal-using":[0],"agents":[1,54,164],"have":[2],"quickly":[3],"become":[4],"the":[5,47,63],"most":[6],"popular":[7],"downstream":[8],"application":[9],"of":[10,25,35,40,108],"language":[11],"models":[12,81,135],"(LMs).":[13],"Despite":[14],"their":[15],"prevalence,":[16],"relatively":[17],"little":[18],"academic":[19,160],"work":[20,161],"has":[21],"examined":[22],"RL-based":[23],"training":[24],"these":[26],"models,":[27,150],"likely":[28],"due":[29],"to":[30,55,62,103],"difficult":[31],"benchmarks,":[32],"a":[33,38,90,142,154],"lack":[34,39],"data,":[36,140,149],"and":[37,97,113,151],"simple":[41],"baseline":[42,156],"recipes.":[43],"We":[44,116,131,146],"present":[45],"Tmax,":[46],"strongest":[48],"open":[49,58,159],"RL":[50,112,137],"recipe":[51,68],"for":[52,111,157],"terminal":[53,109,119,163],"date,":[56],"bringing":[57],"data":[59,88],"recipes":[60],"closer":[61],"frontier.":[64],"While":[65],"simple,":[66,143],"our":[67,118,139,148],"achieves":[69],"27\\%":[70],"on":[71,162],"Terminal-Bench":[72],"2.0":[73],"with":[74,138],"only":[75],"9B":[76],"parameters,":[77],"outperforming":[78],"much":[79],"larger":[80,125],"from":[82],"prior":[83],"work.":[84],"Concretely,":[85],"we":[86],"generate":[87,105],"using":[89,136,141],"novel":[91],"taxonomy,":[92],"combining":[93],"difficulty":[94],"control,":[95],"personas,":[96],"verifier":[98],"diversification,":[99],"which":[100,121],"allows":[101],"us":[102],"cheaply":[104],"large":[106],"amounts":[107],"environments":[110],"SFT":[114],"training.":[115],"open-source":[117],"dataset,":[120],"is":[122],"over":[123],"2.5x":[124],"than":[126],"previously":[127],"released":[128],"terminal-agent":[129],"datasets.":[130],"then":[132],"train":[133],"open-weight":[134],"outcome-only":[144],"recipe.":[145],"release":[147],"code":[152],"as":[153],"strong":[155],"future":[158],"at":[165],"https://github.com/hamishivi/tmax.":[166]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}