通用研究代理可自定义策略，无需训练即可使用任意大模型
Universal Deep Research: Bring Your Own Model and Strategy
- 用通用框架包裹任意语言模型，支持自定义研究策略
- 支持最小、广泛、密集三种研究策略，无需额外训练
- 适合希望灵活定制研究流程的研究人员
深度研究工具是当今最具影响力且最常使用的智能体系统之一。然而，我们观察到目前每种深度研究智能体都硬编码了特定的研究策略和固定工具组合。为此，我们提出通用深度研究（Universal Deep Research, UDR），一种可封装任意语言模型的通用智能体系统，使用户能够无需任何额外训练或微调，自由创建、编辑和优化完全自定义的深度研究策略。为展示系统的通用性，我们为UDR配置了最小化、扩展性和密集型三种示例策略，并提供用户界面以支持系统实验。
原文摘要 · Abstract (English)
Deep research tools are among the most impactful and most commonly encountered agentic systems today. We observe, however, that each deep research agent introduced so far is hard-coded to carry out a particular research strategy using a fixed choice of tools. We introduce Universal Deep Research (UDR), a generalist agentic system that wraps around any language model and enables the user to create, edit, and refine their own entirely custom deep research strategies without any need for additional training or finetuning. To showcase the generality of our system, we equip UDR with example minimal, expansive, and intensive research strategies, and provide a user interface to facilitate experimentation with the system.
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