想找能同时把深挖和广搜做到极致的搜索方法？看WebSwarm怎么用递归多智能体搞定的，测试结果比单智能体强不少。
WebSwarm是一种渐进式递归委托框架，通过动态实例化具有本地目标和搜索模式的智能体搜索节点，实现任务分解、递归扩展和智能体协作。每个节点可自行求解目标或委托子节点，完成后向上返回证据和结果，支持父节点进一步扩展或聚合。在BrowseComp-Plus、WideSearch、DeepWideSearch和GISA四个基准上，WebSwarm在深度、广度及交织任务中持续优于单智能体和多智能体基线。消融实验、难度分析、网络工具效率和模型泛化验证了其有效性。
WebSwarm: Recursive Multi-Agent Orchestration for Deep-and-Wide Web Search
Large language model (LLM)-based web search agents are transforming information seeking from simple factoid question answering into complex, deep-and-wide search and research-oriented tasks. A single ReAct-style agent is constrained by one long trajectory and limited context, making it difficult to handle depth and coverage simultaneously. Existing multi-agent systems improve search coverage through parallel execution and aggregation, but still exhibit clear limitations in recursive depth, collaboration adaptability, and evidence-grounded expansion. We propose WebSwarm, a progressive recursive delegation framework that jointly constructs task decomposition, recursive expansion, and agent collaboration during inference. WebSwarm dynamically instantiates agentic search nodes, each coupling a local objective with a search mode that specifies how the node should organize search and collaboration. Each node can either solve its objective itself or further delegate child nodes; after solving, it returns evidence and results upward, enabling parent nodes to further expand, revise, or aggregate the search process. To guide this process, WebSwarm first probes how task-relevant information is organized on the web to ground subsequent node expansion, and reuses process-level experience across homogeneous sibling nodes. Experiments on BrowseComp-Plus, WideSearch, DeepWideSearch, and GISA show that WebSwarm consistently outperforms single-agent and multi-agent baselines on deep, wide, and interleaved deep-and-wide tasks. Further analyses of ablation, task difficulty, web tool efficiency, and model generalization explain WebSwarm's effectiveness and provide insights for multi-agent search systems.