FlowSearch: Advancing Deep Research with Dynamic Structured Knowledge Flow
Jan 11, 2026·,,,,,,,,,,,,,·
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Yusong Hu
Runmin Ma
Yue Fan
Jinxin Shi
Zongsheng Cao
Yuhao Zhou
Jiakang Yuan
Shuaiyu Zhang
Shiyang Feng
Xiangchao Yan
Shufei Zhang
Wenlong Zhang
Lei Bai
Bo Zhang

Abstract
Deep research is an inherently challenging task that demands both breadth and depth of thinking. It involves navigating diverse knowledge spaces and reasoning over complex, multi-step dependencies, which presents substantial challenges for agentic systems. To address this, we propose FlowSearch, a multi-agent framework that actively constructs and evolves a dynamic structured knowledge flow to drive subtask execution and reasoning. FlowSearch is capable of strategically planning and expanding the knowledge flow to enable parallel exploration and hierarchical task decomposition, while also adjusting the knowledge flow in real time based on feedback from intermediate reasoning outcomes and insights. FlowSearch achieves competitive performance on both general and scientific benchmarks, including GAIA, HLE, GPQA and TRQA, demonstrating its effectiveness in multi-disciplinary research scenarios and its potential to advance scientific discovery
Type
Publication
ACL 2026