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 27…

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: https://arxiv.org/abs/2610.04074 Chat with Paper: https://academy.dair.ai/papers/ideascientist-orchestrating-agents-for-grounded-scientific-ideation-2610.04074

Banger paper from Google Cloud AI Research. If you follow autonomous research agents, this one is worth your time. ScientistTwo takes a prob…
Banger paper from Google on agent harnesses for long-horizon tasks. (bookmark it) Google Research built a many-agent harness for long mathem…
Banger paper from Microsoft Research. (bookmark it) They run 1K+ coding agents at once to test a scalable self-organized multi-agent harness…
NEW paper from Google on multi-agent research agents. It's one of the first systems that handles end-to-end LaTeX generation, targeted liter…

Source: DAIR.AI (X) | 2026-10-10

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