{"id":"https://openalex.org/W7163590744","doi":"https://doi.org/10.48550/arxiv.2606.05080","title":"AutoLab: Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks?","display_name":"AutoLab: Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks?","publication_year":2026,"publication_date":"2026-06-03","ids":{"openalex":"https://openalex.org/W7163590744","doi":"https://doi.org/10.48550/arxiv.2606.05080"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.05080","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05080","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.2606.05080","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028990387","display_name":"Zhangchen Xu","orcid":"https://orcid.org/0000-0002-6971-412X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Zhangchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137820216","display_name":"Junda Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Junda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137886365","display_name":"Yue Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137813932","display_name":"Dongfu Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Dongfu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137859734","display_name":"Jiefeng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jiefeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137898950","display_name":"Hang Hua","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hua, Hang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137914500","display_name":"Zijian Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Zijian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137848926","display_name":"Zheyuan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zheyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069088584","display_name":"Zexue He","orcid":"https://orcid.org/0009-0001-9733-0545"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Zexue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119938349","display_name":"Lichi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Lichi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137813643","display_name":"Shizhe Diao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Diao, Shizhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137809867","display_name":"Jiaxin Pei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pei, Jiaxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137811079","display_name":"Jinsung Yoon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoon, Jinsung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137844247","display_name":"Hao Zhang","orcid":"https://orcid.org/0009-0008-1116-9158"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137855994","display_name":"Mengdi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Mengdi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079723268","display_name":"Radha Poovendran","orcid":"https://orcid.org/0000-0003-0269-8097"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Poovendran, Radha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029380651","display_name":"Misha Sra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sra, Misha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137823016","display_name":"Alex Pentland","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pentland, Alex","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5104078124","display_name":"Zichen Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zichen","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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.1550000011920929,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.1550000011920929,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.12770000100135803,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.06239999830722809,"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/task","display_name":"Task (project management)","score":0.6991999745368958},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6791999936103821},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5507000088691711},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.49810001254081726},{"id":"https://openalex.org/keywords/frontier","display_name":"Frontier","score":0.49459999799728394},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4717000126838684}],"concepts":[{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6991999745368958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6942999958992004},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6791999936103821},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5507000088691711},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.49810001254081726},{"id":"https://openalex.org/C2778571376","wikidata":"https://www.wikidata.org/wiki/Q1355821","display_name":"Frontier","level":2,"score":0.49459999799728394},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4717000126838684},{"id":"https://openalex.org/C51485801","wikidata":"https://www.wikidata.org/wiki/Q16966861","display_name":"Efficient frontier","level":3,"score":0.38940000534057617},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.3878999948501587},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3499000072479248},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33880001306533813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2962999939918518},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2621999979019165},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.25110000371932983},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.05080","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05080","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.2606.05080","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05080","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Scientific":[0],"and":[1,16,81,95,132,168,181],"engineering":[2],"progress":[3],"is":[4,116],"fundamentally":[5],"a":[6,55,89,102],"long-horizon":[7,60,140,190],"iterative":[8,42],"process:":[9],"proposing":[10],"changes,":[11],"running":[12],"experiments,":[13],"measuring":[14],"outcomes,":[15],"continuously":[17],"refining":[18],"artifacts.":[19],"Yet":[20],"existing":[21],"benchmarks":[22],"for":[23,58],"frontier":[24,144],"models":[25,109],"primarily":[26],"evaluate":[27],"either":[28,150],"single-turn":[29],"responses":[30],"or":[31,153],"short-horizon":[32],"agent":[33],"trajectories,":[34],"failing":[35],"to":[36,98,184],"capture":[37],"the":[38,111,118,163,176],"challenges":[39,96],"of":[40,65,114,120,165],"sustained":[41],"improvement":[43],"over":[44],"extended":[45],"time":[46,166],"horizons.":[47],"To":[48],"address":[49],"this":[50],"gap,":[51],"we":[52],"introduce":[53],"AutoLab,":[54],"new":[56],"benchmark":[57],"ultra":[59],"closed-loop":[61],"optimization.":[62,84],"AutoLab":[63],"consists":[64],"36":[66],"realistic,":[67],"expert-curated":[68],"tasks":[69],"spanning":[70],"four":[71],"diverse":[72],"domains:":[73],"system":[74],"optimization,":[75],"puzzle":[76],"&amp;":[77],"challenge,":[78],"model":[79],"development,":[80],"CUDA":[82],"kernel":[83],"Each":[85],"task":[86,182],"begins":[87],"with":[88,157],"correct":[90],"but":[91,125],"deliberately":[92],"suboptimal":[93],"baseline":[94],"agents":[97],"improve":[99],"it":[100],"within":[101],"strict":[103],"wall-clock":[104],"budget.":[105],"Evaluating":[106],"17":[107],"state-of-the-art":[108],"reveals":[110],"dominant":[112],"predictor":[113],"success":[115],"not":[117],"quality":[119],"an":[121],"agent's":[122],"initial":[123],"attempt,":[124],"its":[126],"persistence":[127],"in":[128,171],"repeatedly":[129],"benchmarking,":[130],"editing,":[131],"incorporating":[133],"empirical":[134],"feedback.":[135],"While":[136],"claude-opus-4.6":[137],"exhibits":[138],"strong":[139],"optimization":[141],"capabilities,":[142],"most":[143],"models,":[145],"including":[146],"several":[147],"proprietary":[148],"ones,":[149],"terminate":[151],"prematurely":[152],"exhaust":[154],"their":[155],"budgets":[156],"minimal":[158],"progress.":[159],"These":[160],"results":[161],"underscore":[162],"importance":[164],"awareness":[167],"persistent":[169],"iteration":[170],"autonomous":[172],"agents.":[173,191],"We":[174],"open-source":[175],"full":[177],"benchmark,":[178],"evaluation":[179],"harness,":[180],"artifacts,":[183],"accelerate":[185],"research":[186],"toward":[187],"truly":[188],"capable":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-05T00:00:00"}
