{"schemaVersion":"nuwa-current-record-1","version":"2026-10-29.1","publication":"published","work":{"id":"labbench-two","title":"LABBench2: An Improved Benchmark for AI Systems Performing Biology Research","aliases":["LABBench2"],"authors":["Jon M Laurent","Albert Bou","Michael Pieler","Conor Igoe","Alex Andonian","Siddharth Narayanan","James Braza","Alexandros Sanchez Vassopoulos","Jacob L Steenwyk","Blake Lash","Andrew D White","Samuel G Rodriques"],"primaryFunction":"evaluation","secondaryFunctions":[],"kind":"benchmark","sourceId":"labbench-two-publication","attributionSourceId":"labbench-two-publication-author-source","originalUrl":"https://arxiv.org/abs/2604.09554","publicationDate":"2026-02-04","updatedOn":"2026-10-25","areas":["cbrn"],"scopeNote":{"en":"The main dimension follows the task outcome in the original protocol. Topic relevance is documented in the parent research record; no unreviewed question-level links are inferred.","zh":"主维度依据原协议的任务结果确定。主题关联见研究档案，不推断尚未审阅的问题级关联。"},"protocolIds":["labbench-two"],"contributions":[{"organizationId":"edison","role":"research","sourceId":"labbench-two-publication-author-source","locator":"Author affiliations on the original paper title page"},{"organizationId":"futurehouse","role":"research","sourceId":"labbench-two-publication-author-source","locator":"Author affiliations on the original paper title page"}],"summary":{"en":"Evaluates biology-research tasks to study AI assistance with scientific work rather than only factual recall.","zh":"通过生物学研究任务，考察 AI 对科学工作的辅助能力，而非仅测试事实回忆。"},"note":{"question":null,"method":null,"finding":null,"supports":null,"limits":null,"connections":null},"resources":[],"noteStatus":{"question":"limited","method":"limited","finding":"limited","supports":"limited","limits":"limited","connections":"limited"},"noteAvailability":{"en":"A substantive NUWA research note is not yet available. The repeated draft sections were removed pending review of the original methods, findings and limitations; use the original publication for the research account.","zh":"实质性的 NUWA 研究笔记尚未完成。重复草稿章节已移除，待核查原始方法、发现与限制；研究内容请以原始出版物为准。"},"noteSourceLocator":"No complete section-level method/results/limitations review completed for this note; cached original page and any chart audit retained as discovery evidence.","tags":[]},"reading":{"id":"labbench-two","title":"LABBench2: An Improved Benchmark for AI Systems Performing Biology Research","en":{"question":"Can scientific capability tests better approximate useful research work than multiple-choice knowledge questions?","design":"LABBench2 contains over 1,900 tasks across research-support skills, comparing models with and without tools in more realistic contexts.","findings":["The authors report model-specific subtask accuracy differences of −26% to −46% relative to the earlier benchmark.","Tool augmentation helps variably rather than uniformly (§3)."],"interpretation":"NUWA interpretation: changing realism can reveal gaps hidden by improving scores on older task formats.","limits":"Wet-lab execution, ambiguous goals and days-long iteration remain simplified; verifier reliability and biological breadth are limited (§4.3).","decisionRelevance":"Model recommendation: use version- and tool-specific results; do not infer operational biological uplift from these scores.","takeaway":"NUWA interpretation: changing realism can reveal gaps hidden by improving scores on older task formats.","connections":[],"scoring":"Research-support task accuracy, with base-model and tool-augmented conditions reported separately.","conditions":"More than 1,900 tasks; practical research is still simplified.","statistics":"The authors report model-specific subtask accuracy differences of −26% to −46% relative to the earlier benchmark. Tool augmentation helps variably rather than uniformly (§3).","usage":"Model recommendation: use version- and tool-specific results; do not infer operational biological uplift from these scores."},"zh":{"question":"科研能力测试能否比知识选择题更接近有用研究工作？","design":"LABBench2含逾1,900项研究支持任务，在更真实语境比较有工具与无工具模型。","findings":["作者报告相较旧基准，模型各子任务正确率差异为−26%至−46%。","工具增强效果不一致（§3）。"],"interpretation":"NUWA 解读：提高真实性可暴露旧格式得分上升所隐藏的缺口。","limits":"湿实验执行、模糊目标和跨日迭代仍被简化，验证器及领域广度有限（§4.3）。","decisionRelevance":"模型建议：使用具体版本与工具条件，不据此推断操作性生物能力增益。","takeaway":"NUWA 解读：提高真实性可暴露旧格式得分上升所隐藏的缺口。","connections":[],"scoring":"研究支持任务正确率，分无工具及工具增强条件。","conditions":"逾1,900任务，实际研究仍被简化。","statistics":"作者报告相较旧基准，模型各子任务正确率差异为−26%至−46%。 工具增强效果不一致（§3）。","usage":"模型建议：使用具体版本与工具条件，不据此推断操作性生物能力增益。"},"assertionPolicy":{"question":"source-research-question","design":"source-finding","findings":"source-finding","interpretation":"nuwa-interpretation","limits":"source-limit-or-explicit-editorial-scope-limit","connections":"source-supported-relationship-only","decisionRelevance":"model-recommendation-not-source-conclusion"},"sourceRefs":[{"sourceId":"labbench-two-publication-author-source","url":"https://arxiv.org/html/2604.09554","locator":"Abstract","version":"Selected original resource https://arxiv.org/html/2604.09554; sha256:333fb7f67888029041cb7ff7df47ada35844806b30ea09197b5258442e65aa72; archived source capture; exact capture time not independently established","artifactSha256":"333fb7f67888029041cb7ff7df47ada35844806b30ea09197b5258442e65aa72"},{"sourceId":"labbench-two-publication-author-source","url":"https://arxiv.org/html/2604.09554","locator":"§3 Results","version":"Selected original resource https://arxiv.org/html/2604.09554; sha256:333fb7f67888029041cb7ff7df47ada35844806b30ea09197b5258442e65aa72; archived source capture; exact capture time not independently established","artifactSha256":"333fb7f67888029041cb7ff7df47ada35844806b30ea09197b5258442e65aa72"},{"sourceId":"labbench-two-publication-author-source","url":"https://arxiv.org/html/2604.09554","locator":"§4.3 Limitations and future work","version":"Selected original resource https://arxiv.org/html/2604.09554; sha256:333fb7f67888029041cb7ff7df47ada35844806b30ea09197b5258442e65aa72; archived source capture; exact capture time not independently established","artifactSha256":"333fb7f67888029041cb7ff7df47ada35844806b30ea09197b5258442e65aa72"}],"publication":{"state":"published","publishedOn":"2026-10-29","authorizationReference":"user-authorized-global-index-publication-2026-10-29","reviewedCandidateId":"local-6efe31bc4a0c0f37"},"review":{"state":"published-note","sourceScope":"full-text","availableScope":null,"readingCoverage":"selected-source-sections; not a complete section-by-section paper audit","completePaperAudit":false,"independentEvidenceReview":"pending-human-review","bilingualEditorialReview":"pending-human-review","authorship":"model-assisted-research-note","preparedFingerprint":"bee5c40f957043824e21b3904c2c5109c456e8f86eb0b7f13ceedb3fb8317858"}},"sources":[{"id":"labbench-two-publication","title":"LABBench2: An Improved Benchmark for AI Systems Performing Biology Research","url":"https://arxiv.org/abs/2604.09554","version":"arXiv:2604.09554v2","publicationDate":"2026-02-04","datePrecision":"day","type":"paper","verifiedOn":"2026-10-25","documentId":"arxiv:2604.09554","authors":["Jon M Laurent","Albert Bou","Michael Pieler","Conor Igoe","Alex Andonian","Siddharth Narayanan","James Braza","Alexandros Sanchez Vassopoulos","Jacob L Steenwyk","Blake Lash","Andrew D White","Samuel G Rodriques"],"aliases":["https://doi.org/10.48550/arXiv.2604.09554","https://arxiv.org/abs/2604.09554","https://arxiv.org/pdf/2604.09554"]}]}