{"id":"https://openalex.org/W7165033905","doi":"https://doi.org/10.48550/arxiv.2606.17682","title":"From Trainee to Trainer: LLM-Designed Training Environment for RL with Multi-Agent Reasoning","display_name":"From Trainee to Trainer: LLM-Designed Training Environment for RL with Multi-Agent Reasoning","publication_year":2026,"publication_date":"2026-06-16","ids":{"openalex":"https://openalex.org/W7165033905","doi":"https://doi.org/10.48550/arxiv.2606.17682"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.17682","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17682","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.2606.17682","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138817247","display_name":"Chao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138807807","display_name":"Chengzu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Chengzu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138789257","display_name":"Zhiwei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zhiwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138827275","display_name":"Yinhong Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yinhong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138792666","display_name":"Zhijiang Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Zhijiang","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/T10028","display_name":"Topic Modeling","score":0.4172999858856201,"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/T10028","display_name":"Topic Modeling","score":0.4172999858856201,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.13349999487400055,"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/T13629","display_name":"Text Readability and Simplification","score":0.057100001722574234,"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/testbed","display_name":"Testbed","score":0.671500027179718},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6385999917984009},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6105999946594238},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6011999845504761},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5511000156402588},{"id":"https://openalex.org/keywords/learning-environment","display_name":"Learning environment","score":0.4616999924182892}],"concepts":[{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.671500027179718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6700999736785889},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6385999917984009},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6105999946594238},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6011999845504761},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5511000156402588},{"id":"https://openalex.org/C2778365744","wikidata":"https://www.wikidata.org/wiki/Q2426689","display_name":"Learning environment","level":2,"score":0.4616999924182892},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4018999934196472},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.35850000381469727},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.33959999680519104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31690001487731934},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.28769999742507935},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.2865999937057495},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.17682","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17682","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.2606.17682","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17682","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reinforcement":[0],"learning":[1,183],"pipelines":[2],"for":[3,77,108],"Large":[4],"Language":[5],"Model":[6],"(LLM)":[7],"training":[8,58,111,137],"often":[9],"rely":[10,154],"on":[11,91,125,155],"manually":[12],"redesigned":[13],"environments":[14],"between":[15],"stages,":[16],"requiring":[17],"practitioners":[18],"to":[19,55,188],"heuristically":[20],"infer":[21],"which":[22,40,103,142],"configuration":[23,107],"will":[24],"best":[25],"improve":[26],"the":[27,36,41,56,88,106,109,116,121,165,176,185],"current":[28,42,166],"policy.":[29],"To":[30],"automate":[31],"this":[32,84],"process,":[33],"we":[34,86],"propose":[35],"LLM-as-Environment-Engineer":[37],"framework":[38,119],"in":[39],"policy":[43,95,182],"model":[44],"analyzes":[45],"failure":[46,97,156],"trajectories":[47],"together":[48],"with":[49],"contextual":[50],"information":[51],"and":[52,79,99,135,158],"proposes":[53],"modifications":[54],"next-stage":[57],"environment":[59,72,81,89,100,152,173],"configuration.":[60],"We":[61,139],"also":[62],"introduce":[63],"MAPF-FrozenLake,":[64],"a":[65,171],"controllable":[66],"testbed":[67],"whose":[68],"generator":[69],"exposes":[70],"multi-dimensional":[71],"configurations,":[73],"making":[74],"it":[75,104],"suitable":[76],"studying":[78],"benchmarking":[80],"redesign.":[82],"On":[83],"testbed,":[85],"condition":[87],"engineer":[90,174],"structured":[92],"summaries":[93],"of":[94,144],"behavior,":[96],"cases,":[98],"statistics,":[101],"from":[102],"produces":[105],"next":[110],"stage.":[112],"With":[113],"Qwen3-4B":[114],"as":[115,170],"backbone,":[117],"our":[118,126],"achieves":[120],"strongest":[122],"aggregate":[123],"performance":[124],"benchmarks,":[127],"outperforming":[128],"larger":[129],"proprietary":[130],"LLMs":[131],"(e.g.,":[132],"GPT,":[133],"Gemini)":[134],"fixed-environment":[136],"baselines.":[138],"further":[140],"analyze":[141],"forms":[143],"context":[145],"are":[146],"most":[147],"effective,":[148],"finding":[149],"that":[150,161,181],"successful":[151],"updates":[153],"evidence":[157],"preserve":[159],"configurations":[160],"already":[162],"work.":[163],"Interestingly,":[164],"RL":[167],"checkpoint":[168],"serves":[169],"better":[172],"than":[175],"original":[177],"base":[178],"model,":[179],"suggesting":[180],"improves":[184],"model's":[186],"ability":[187],"diagnose":[189],"its":[190],"remaining":[191],"weaknesses.":[192]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-18T00:00:00"}
