SAIL: Scientific Agentic Intelligence via a Science-Aware Loop
We introduce SAIL, an open model with 35B total and 3B active parameters for literature research, scientific coding, and multi-step research workflows. SAIL is developed through a science-aware improvement loop: agents built on frontier AI models analyze its task failures and construct training tasks that address the underlying capability gaps. The diagnosis examines search and evidence selection in literature tasks, scientific assumptions and reasoning in coding, and planning and revision in longer investigations. The agents draw on paper collections and scientific code repositories to build problems, interaction trajectories, and executable tasks with the required environments and tools...
| Authors | SAIL Model Team, Boyuan Sun, Bryan Dai et al. |
|---|---|
| Primary category | cs.CL |
| Published | 8 October 2026 |
| Last updated at source | 10 October 2026 |
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