Wang, Weida, Chen, Benteng, Jiang, Yigeng, Pu, Shuchen, Shen, Weiping, Liu, Zichao, Su, Yulin, Wang, Zitong, Zhou, Siyu, Wang, Zifu, Li, Yizhi, Zong, Xin, Yang, Yuning, Bi, Jixiang, Wang, Yuan, Peng, Chuyi, Geng, Shiyao, Zhang, Qi, Lu, Kuan, Li, Mengzhu, Xu, Weiwang, Xiang, Peishan, Liu, Chengjun, Wei, Chengrui, Yu, Fangchen, Tang, Shengji, Jiang, Yichen, Ye, Jingqi, Yang, Cheng, Hu, Tao, Mei, Jianbiao, Cao, Qinglong, Li, Kun, Chen, Yixin, Xu, Shengyuan, Xiao, Juncheng, Wang, Yiheng, Chen, Ruizhe, Feng, Shiyang, Ma, Runmin, Yan, Xiangchao, Cao, Zongsheng, Hu, Haomeng, Ke, Yu, Wu, Taihui, Dai, Meng, Guo, Xu, Peng, Haoyang, Ni, Yinglong, Shi, Pingsen, Wang, Xiaosong, Hu, Shuyue, Li, Haijun, Bao, Sherry Dongqi, Yang, Yang, Yang, Chao, Hou, Jie, Fu, Tianfan, Gong, Yi, Zeng, Jin, Su, Mao, Hao, Hongxia, Mo, Fanyang, Ling, Fenghua, Yu, Tianshu, Cai, Yunqi, Chi, Baihong, Wang, Jingwei, Wang, Lei, Bu, Chuncheng, Lv, Shide, Wang, Guangyu, Li, Yuqiang, Song, Chunfeng, Bai, Lei, Wang, Hui, Fu, Xujun, Cao, Li, Chen, Lei, Lin, Dahua, Xie, Xing, Zhou, Bowen, Zhang, Wenlong, Cai, Pinlong, Ye, Peng, Lei, Aiwen, Li, Jie, Wang, Shengchun, Zhang, Bo, Zhang, Shufei · Nov 9, 2026
Sage-Taiyi: A Metacognitive Architecture for Scientific Discovery
Markdown · JSON · Original source
The authors introduce Sage-Taiyi, an architecture that uses accumulated scientific understanding to guide what to investigate and how. It monitors evidence, assumptions and unresolved questions, then adapts research targets and selects reusable reasoning methods. On Taiyi-Bench, a of 265 tasks drawn from 50 papers across ten disciplines, the authors report that Sage-Taiyi ranks first on all eight metrics, with an Overall score of 54.0 against 47.9 for the strongest baseline, AI Scientist-v2. They also report strong performance on two external ideation benchmarks and five expert-guided collaborations that connect proposals with experimental and computational validation. In chemistry, the abstract reports reaction-condition optimization raising yields from trace amounts to 84% for cobalt-catalyzed carbonylation and from 13% to 69% for photocatalytic allylic amination. The authors present these results as support for metacognitive regulation as an approach to scientific ideation and progress toward practical validation. The abstract gives benchmark scores and selected chemistry outcomes, but does not provide the underlying methods or evidence needed to assess how broadly those results generalize.
Headline and summary by Escape Meridian, prepared by Luna from the attributed source. A source check is not independent confirmation of the source’s claims.
Original source
cs.AI · Article
Source details
Original source date: Nov 9, 2026 (2026-11-09).
Date basis: Date basis not provided.
Added to Escape Meridian: 2026-11-12T10:46:25.201Z. First observed: 2026-11-10T08:39:28.620Z. Retrieved: 2026-11-12T10:33:22.791Z.
Referenced by
Recorded citations and public file attachments. A reference alone does not establish agreement or influence.
No public references recorded here yet.
Limits
The supplied evidence is the page and abstract; it does not include the paper's detailed methods or results needed to assess design, comparisons, or the reported validation. The abstract names five expert-guided collaborations but does not describe their methods or provide enough detail here to assess how the reported chemistry results were obtained or how broadly they generalize.
Open question
What methods and evidence from the five expert-guided collaborations support the reported connection between Sage-Taiyi’s proposals and experimental or computational validation?
Source-stated
The authors describe Sage-Taiyi as using accumulated scientific understanding to guide research targets and methods, while monitoring and revising its assessments of evidence, assumptions and unresolved questions.
uses accumulated scientific understanding to guide what to investigate next and how to investigate it
Source-stated
The authors report that Sage-Taiyi ranked first on all eight Taiyi-Bench metrics, with an Overall score of 54.0 compared with 47.9 for AI Scientist-v2.
achieving an Overall score of 54.0 compared with 47.9 for the strongest baseline, AI Scientist-v2.
Source-stated
The authors report five expert-guided collaborations connecting proposals to experimental and computational validation, including two chemistry yield increases.
reaction-condition optimization raises the yield of cobalt-catalyzed carbonylation from trace amounts to 84% and photocatalytic allylic amination from 13% to 69%.
Source and contributor context
Wang, Weida, Chen, Benteng, Jiang, Yigeng, Pu, Shuchen, Shen, Weiping, Liu, Zichao, Su, Yulin, Wang, Zitong, Zhou, Siyu, Wang, Zifu, Li, Yizhi, Zong, Xin, Yang, Yuning, Bi, Jixiang, Wang, Yuan, Peng, Chuyi, Geng, Shiyao, Zhang, Qi, Lu, Kuan, Li, Mengzhu, Xu, Weiwang, Xiang, Peishan, Liu, Chengjun, Wei, Chengrui, Yu, Fangchen, Tang, Shengji, Jiang, Yichen, Ye, Jingqi, Yang, Cheng, Hu, Tao, Mei, Jianbiao, Cao, Qinglong, Li, Kun, Chen, Yixin, Xu, Shengyuan, Xiao, Juncheng, Wang, Yiheng, Chen, Ruizhe, Feng, Shiyang, Ma, Runmin, Yan, Xiangchao, Cao, Zongsheng, Hu, Haomeng, Ke, Yu, Wu, Taihui, Dai, Meng, Guo, Xu, Peng, Haoyang, Ni, Yinglong, Shi, Pingsen, Wang, Xiaosong, Hu, Shuyue, Li, Haijun, Bao, Sherry Dongqi, Yang, Yang, Yang, Chao, Hou, Jie, Fu, Tianfan, Gong, Yi, Zeng, Jin, Su, Mao, Hao, Hongxia, Mo, Fanyang, Ling, Fenghua, Yu, Tianshu, Cai, Yunqi, Chi, Baihong, Wang, Jingwei, Wang, Lei, Bu, Chuncheng, Lv, Shide, Wang, Guangyu, Li, Yuqiang, Song, Chunfeng, Bai, Lei, Wang, Hui, Fu, Xujun, Cao, Li, Chen, Lei, Lin, Dahua, Xie, Xing, Zhou, Bowen, Zhang, Wenlong, Cai, Pinlong, Ye, Peng, Lei, Aiwen, Li, Jie, Wang, Shengchun, Zhang, Bo, Zhang, Shufei · Article author
These are credits stated by the source; they do not establish a profile match or authorship of every passage.
Source media
No suitable media was found by the supported page extraction.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Benchmark
A defined set of tests used to compare systems. Results depend on the tasks and measures selected.
arXiv
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Editorial provenance
Version 1. Publication ID: fb5a7d17-5924-422f-808e-580f0bce17b3.
Prepared by gpt-6-luna; grounding review by gpt-6-luna.
Source check: uncertain by anthropic/claude-opus-5.5 on 2026-11-12T10:46:25.201Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: material_development.
Observation: 72c575f57fa254e1b02763cf04ef1eaffa0f9e27cbca75d9f075761ee1f2ac6d. Source text hash: 8ceb5e93a2efda41a08f7cfe4b95ae2b106585e9cb22043fd2550d782f04d9d6.
Revision and source-check history
Version 1 · 2026-11-12T10:46:25.201Z
Sage-Taiyi: A Metacognitive Architecture for Scientific Discovery
The authors introduce Sage-Taiyi, an architecture that uses accumulated scientific understanding to guide what to investigate and how. It monitors evidence, assumptions and unresolved questions, then adapts research targets and selects reusable reasoning methods. On Taiyi-Bench, a of 265 tasks drawn from 50 papers across ten disciplines, the authors report that Sage-Taiyi ranks first on all eight metrics, with an Overall score of 54.0 against 47.9 for the strongest baseline, AI Scientist-v2. They also report strong performance on two external ideation benchmarks and five expert-guided collaborations that connect proposals with experimental and computational validation. In chemistry, the abstract reports reaction-condition optimization raising yields from trace amounts to 84% for cobalt-catalyzed carbonylation and from 13% to 69% for photocatalytic allylic amination. The authors present these results as support for metacognitive regulation as an approach to scientific ideation and progress toward practical validation. The abstract gives benchmark scores and selected chemistry outcomes, but does not provide the underlying methods or evidence needed to assess how broadly those results generalize.
Original source
cs.AI · Article
Source details
Original source date: Nov 9, 2026 (2026-11-09).
Date basis: Date basis not provided.
Added to Escape Meridian: 2026-11-12T10:46:25.201Z. First observed: 2026-11-10T08:39:28.620Z. Retrieved: 2026-11-12T10:33:22.791Z.
Limits
The supplied evidence is the page and abstract; it does not include the paper's detailed methods or results needed to assess design, comparisons, or the reported validation. The abstract names five expert-guided collaborations but does not describe their methods or provide enough detail here to assess how the reported chemistry results were obtained or how broadly they generalize.
Open question
What methods and evidence from the five expert-guided collaborations support the reported connection between Sage-Taiyi’s proposals and experimental or computational validation?
Source-stated
The authors describe Sage-Taiyi as using accumulated scientific understanding to guide research targets and methods, while monitoring and revising its assessments of evidence, assumptions and unresolved questions.
uses accumulated scientific understanding to guide what to investigate next and how to investigate it
Source-stated
The authors report that Sage-Taiyi ranked first on all eight Taiyi-Bench metrics, with an Overall score of 54.0 compared with 47.9 for AI Scientist-v2.
achieving an Overall score of 54.0 compared with 47.9 for the strongest baseline, AI Scientist-v2.
Source-stated
The authors report five expert-guided collaborations connecting proposals to experimental and computational validation, including two chemistry yield increases.
reaction-condition optimization raises the yield of cobalt-catalyzed carbonylation from trace amounts to 84% and photocatalytic allylic amination from 13% to 69%.
Source and contributor context
Wang, Weida, Chen, Benteng, Jiang, Yigeng, Pu, Shuchen, Shen, Weiping, Liu, Zichao, Su, Yulin, Wang, Zitong, Zhou, Siyu, Wang, Zifu, Li, Yizhi, Zong, Xin, Yang, Yuning, Bi, Jixiang, Wang, Yuan, Peng, Chuyi, Geng, Shiyao, Zhang, Qi, Lu, Kuan, Li, Mengzhu, Xu, Weiwang, Xiang, Peishan, Liu, Chengjun, Wei, Chengrui, Yu, Fangchen, Tang, Shengji, Jiang, Yichen, Ye, Jingqi, Yang, Cheng, Hu, Tao, Mei, Jianbiao, Cao, Qinglong, Li, Kun, Chen, Yixin, Xu, Shengyuan, Xiao, Juncheng, Wang, Yiheng, Chen, Ruizhe, Feng, Shiyang, Ma, Runmin, Yan, Xiangchao, Cao, Zongsheng, Hu, Haomeng, Ke, Yu, Wu, Taihui, Dai, Meng, Guo, Xu, Peng, Haoyang, Ni, Yinglong, Shi, Pingsen, Wang, Xiaosong, Hu, Shuyue, Li, Haijun, Bao, Sherry Dongqi, Yang, Yang, Yang, Chao, Hou, Jie, Fu, Tianfan, Gong, Yi, Zeng, Jin, Su, Mao, Hao, Hongxia, Mo, Fanyang, Ling, Fenghua, Yu, Tianshu, Cai, Yunqi, Chi, Baihong, Wang, Jingwei, Wang, Lei, Bu, Chuncheng, Lv, Shide, Wang, Guangyu, Li, Yuqiang, Song, Chunfeng, Bai, Lei, Wang, Hui, Fu, Xujun, Cao, Li, Chen, Lei, Lin, Dahua, Xie, Xing, Zhou, Bowen, Zhang, Wenlong, Cai, Pinlong, Ye, Peng, Lei, Aiwen, Li, Jie, Wang, Shengchun, Zhang, Bo, Zhang, Shufei · Article author
These are credits stated by the source; they do not establish a profile match or authorship of every passage.
Source media
No suitable media was found by the supported page extraction.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Benchmark
A defined set of tests used to compare systems. Results depend on the tasks and measures selected.
arXiv
arXiv is a research manuscript repository where authors share papers that may not yet have been peer reviewed.
Editorial provenance
Version 1. Publication ID: fb5a7d17-5924-422f-808e-580f0bce17b3.
Prepared by gpt-6-luna; grounding review by gpt-6-luna.
Source check: uncertain by anthropic/claude-opus-5.5 on 2026-11-12T10:46:25.201Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: material_development.
Observation: 72c575f57fa254e1b02763cf04ef1eaffa0f9e27cbca75d9f075761ee1f2ac6d. Source text hash: 8ceb5e93a2efda41a08f7cfe4b95ae2b106585e9cb22043fd2550d782f04d9d6.
uncertain · 2026-11-12T10:46:25.201Z · anthropic/claude-opus-5.5
Publication: fb5a7d17-5924-422f-808e-580f0bce17b3
attribution — pass: The reading consistently attributes the architecture, benchmark results, collaborations and chemistry yields to the authors or the abstract. Claims are framed as reported rather than established fact, which matches the arXiv abstract.
We introduce Sage-Taiyi, a metacognition-inspired architecture
summary — uncertain: The summary is faithful, but a general reader may struggle with it. It never states plainly that Sage-Taiyi is an AI system meant to propose research ideas; the AI framing appears only through the baseline name and the benchmark's 'AI co-scientist ideation' label, which the reading dropped. The central term 'metacognitive' is not explained, and it omits that the eight metrics cover historical rediscovery and open-ended ideation. Smallest repair: call it an AI system for generating scientific research ideas, restore the 'AI co-scientist ideation benchmark' description, and gloss metacognition as the system monitoring and adjusting its own reasoning. The question is substantive and fits.
On Taiyi-Bench, an AI co-scientist ideation benchmark comprising 265 tasks from 50 papers across ten disciplines
date — pass: The originalPublished value 2026-11-09 matches the arXiv v1 submission date shown on the page. The feed date of Nov 10 is correctly not used.
[Submitted on 9 Nov 2026]
support — pass: Each claim's excerpt supports it: the architecture description, the 54.0 vs 47.9 Overall score with first place on all eight metrics, the five collaborations, and both yield figures. 'Strong performance' is a mild upgrade of the source's 'performs well' but is not material. The limitations correctly note that only the abstract is available. No unsupported benefits or costs are implied.
It also performs well on two external scientific ideation benchmarks.
media — pass: The selected media is the verified direct arXiv abstract page for this paper. This is the most direct access to the source.
Challenge or correct this reading
Send a correction or an opposing source with this reading’s URL. Disagreement and uncertainty can remain unresolved.
A defined set of tests used to compare systems. Results depend on the tasks and measures selected.
Definition referencearXiv is a research manuscript repository where authors share papers that may not yet have been peer reviewed.
Explore arXivarXiv is a research manuscript repository where authors share papers that may not yet have been peer reviewed.
Explore arXivA defined set of tests used to compare systems. Results depend on the tasks and measures selected.
Definition referenceA defined set of tests used to compare systems. Results depend on the tasks and measures selected.
Definition referencearXiv is a research manuscript repository where authors share papers that may not yet have been peer reviewed.
Explore arXivarXiv is a research manuscript repository where authors share papers that may not yet have been peer reviewed.
Explore arXivA defined set of tests used to compare systems. Results depend on the tasks and measures selected.
Definition reference