InfoSeeker: A Scalable Hierarchical Parallel Agent Framework for Web Information Seeking

ArXi:2604.02971v1 Announce Type: new Recent agentic search systems have made substantial progress by emphasising deep, multi-step reasoning. However, this focus often overlooks the challenges of wide-scale information synthesis, where agents must aggregate large volumes of heterogeneous evidence across many sources. As a result, most existing large language model agent systems face severe limitations in data-intensive settings, including context saturation, cascading error propagation, and high end-to-end latency.