Sage-A1.5: From Long-Horizon Execution to Scientific Exploration with Capability Composition· Sage-A1.5：从长程执行到科学探索
In this report, we introduce Sage-A1.5, a 35B Mixture-of-Experts agentic model that builds on A1 to advance long-horizon problem solving through adaptive capability composition. Compared with A1, Sage-A1.5 learns not only to solve individual tasks, but also to organize work and revise its approach during execution. Sage-A1.5 highlights three improvements: agentic orchestration, verification, and open scientific discovery. First, agentic orchestration extends single-agent execution through task delegation and parallel collaboration among subagents with isolated contexts, enabling complex tasks to be decomposed and addressed concurrently and supporting efficient execution while reducing interference across concurrent subagents. Second, agentic verification strengthens long-horizon reliabilit
Sage-A1.5 通过能力组合改进了长时解决问题的能力。
- 核心方法
- Sage-A1.5 采用混合专家系统和代理模型，通过任务分配、并行协作和代理验证等技术改进了长时任务的执行效率和可靠性。
- 适合谁读
- 研究者
- 要解决的问题
- 现有的AI模型在解决长时任务时缺乏灵活的策略调整和任务分解能力。
- 关键实验
- 未提供
- 主要贡献
- 实现了单代理到多代理执行的扩展，增强了任务分解和并行处理能力，以及长时任务的可靠性。
- 意义与局限
- Sage-A1.5 的提出对于推进科学探索和复杂任务处理具有重要意义，但在实际应用中可能面临效率和稳定性的问题。