{"id":"https://openalex.org/W7162785433","doi":"https://doi.org/10.48550/arxiv.2605.29559","title":"LiteCoder-Terminal: Scaling Long-Horizon Terminal Environments for Learning Language Agents","display_name":"LiteCoder-Terminal: Scaling Long-Horizon Terminal Environments for Learning Language Agents","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7162785433","doi":"https://doi.org/10.48550/arxiv.2605.29559"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.29559","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29559","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":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.2605.29559","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137315982","display_name":"Xiaoxuan Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Xiaoxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137313433","display_name":"Kaiqi Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Kaiqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137350312","display_name":"Xinyu Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Xinyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137370526","display_name":"Boxi Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Boxi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137370591","display_name":"Yaojie Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Yaojie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137376017","display_name":"Hongyu Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Hongyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137312974","display_name":"Xianpei Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Xianpei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137325586","display_name":"Le Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Le","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/T10181","display_name":"Natural Language Processing Techniques","score":0.34209999442100525,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.34209999442100525,"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":0.1907999962568283,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.12600000202655792,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.8335999846458435},{"id":"https://openalex.org/keywords/verifiable-secret-sharing","display_name":"Verifiable secret sharing","score":0.7591999769210815},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6822999715805054},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6697999835014343},{"id":"https://openalex.org/keywords/terminal","display_name":"Terminal (telecommunication)","score":0.6212999820709229},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5665000081062317},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5460000038146973}],"concepts":[{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.8335999846458435},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.7591999769210815},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7447999715805054},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6822999715805054},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6697999835014343},{"id":"https://openalex.org/C2779664074","wikidata":"https://www.wikidata.org/wiki/Q3518405","display_name":"Terminal (telecommunication)","level":2,"score":0.6212999820709229},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5665000081062317},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5460000038146973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5016000270843506},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4519999921321869},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.40049999952316284},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33009999990463257},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3082999885082245},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.305400013923645},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.2768999934196472}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.29559","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29559","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":"doi:10.48550/arxiv.2605.29559","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29559","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4053497016429901,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Mastering":[0],"terminal":[1,56],"environments":[2,58,84,134,147],"requires":[3],"language":[4],"agents":[5,19,99],"capable":[6],"of":[7,39,91],"multi-step":[8],"planning,":[9],"feedback-grounded":[10],"execution,":[11],"and":[12,36,54,79,113,121,151],"dynamic":[13],"state":[14],"adaptation.":[15],"However,":[16],"training":[17,57],"such":[18],"is":[20],"currently":[21],"bottlenecked":[22],"by":[23],"a":[24,46,149],"reliance":[25],"on":[26,94,116,131],"scraped":[27],"external":[28],"repositories,":[29],"which":[30],"limits":[31],"domain":[32,61],"diversity,":[33],"environment":[34],"controllability,":[35],"the":[37],"targeting":[38],"specific":[40],"capability":[41],"deficits.":[42],"We":[43],"introduce":[44],"LiteCoder-Terminal-Gen,":[45],"zero-dependency":[47],"synthesis":[48],"pipeline":[49],"that":[50,100,143],"autonomously":[51],"generates":[52],"executable":[53,146],"verifiable":[55,83,152],"directly":[59],"from":[60],"specifications.":[62],"Using":[63],"this":[64],"framework,":[65],"we":[66],"construct":[67],"two":[68],"large-scale":[69],"resources:":[70],"LiteCoder-Terminal-SFT,":[71],"comprising":[72],"11,255":[73],"expert":[74],"trajectories":[75],"across":[76],"10":[77],"domains,":[78],"LiteCoder-Terminal-RL,":[80],"featuring":[81],"602":[82],"for":[85,155],"trajectory-level":[86],"preference":[87],"optimization.":[88],"Supervised":[89],"fine-tuning":[90],"Qwen-family":[92],"models":[93],"our":[95,107,132],"SFT":[96],"dataset":[97],"yields":[98,135],"significantly":[101],"outperform":[102],"their":[103],"base":[104],"counterparts.":[105],"Notably,":[106],"32B":[108],"variant":[109],"achieves":[110],"29.06%,":[111],"18.54%,":[112],"34.00%":[114],"pass@1":[115],"Terminal":[117],"Bench":[118],"1.0,":[119],"2.0,":[120],"Pro,":[122],"respectively.":[123],"Furthermore,":[124],"applying":[125],"Direct":[126],"Multi-turn":[127],"Preference":[128],"Optimization":[129],"(DMPO)":[130],"RL":[133],"additional":[136],"performance":[137],"gains.":[138],"These":[139],"results":[140],"systematically":[141],"demonstrate":[142],"fully":[144],"synthetic,":[145],"offer":[148],"scalable":[150],"supervision":[153],"signal":[154],"mastering":[156],"complex,":[157],"real-world":[158],"command-line":[159],"workflows.":[160]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-30T00:00:00"}
