Meta 论文提出 IdeaScientist：27B 开源模型在 AI 研究智能体上超越 Claude Code 与 Codex 方案
DAIR.AI 转发 Meta 关于 AI 研究智能体的论文，其 27B 开源模型在自动科研任务上比最强开源 autoresearch 基线高 14.0%（主要体现在新颖性），并比 Claude Code SDK 和 Codex SDK 方案最高高出 5.9%。
Banger paper from Meta on AI research agents.
(bookmark it)
If you build AI-scientist systems, this one is worth your time.
The result:
A 27B open model beats the strongest open autoresearch baseline by 14.0%, mostly on novelty, and beats Claude Code SDK and Codex SDK setups by up to 5.9%.
How it works:
IdeaScientist splits ideation into three roles trained separately with RL. A gap finder reads related work for limitations, an innovator retrieves mechanisms that solved similar problems in other fields, and a writer turns the result into a full proposal.
Retrieval runs over a corpus of 2.77M decomposed research ideas.
The evaluation only allows literature published before a cutoff date and scores proposals against directions explored later in 15K human-written papers.
Paper: arxiv.org/abs/2610.04074
Chat with Paper: academy.dair.ai/papers/ideas…
来源：dair_ai · x.com