InfoAgent: Advancing Autonomous Information-Seeking Agents
Building Large Language Model agents that expand their capabilities by
interacting with external tools represents a new frontier in AI research and
applications. In this paper, we introduce InfoAgent, a deep research agent
powered by an innovative data synthesis pipeline and orchestrated web search
tools. To construct challenging, hard-to-find queries,we build entity trees and
apply sub-tree sampling with entity fuzzification to systematically increase
question difficulty. Unlike prior work that relies heavily on commercial search
tools, we develop a dedicated self-hosted search infrastructure, enhancing
transparency of agent environments and facilitating further advancement of
agent capacity. We evaluate the effectiveness of our data pipeline by measuring
the average number of tool calls required to correctly answer a question, and
also show that our agent yields better performance when equipped with our
tools. Our InfoAgent is post-trained from Qwen3-14B using a two-stage
recipe: cold-start supervised finetuning to instill long-horizon search
behaviors, followed by reinforcement learning which significantly improves
reasoning-driven tool use. With our methods, InfoAgent achieves 15.3\% accuracy
on BrowseComp, 29.2\% on BrowseComp-ZH, and 40.4\% on Xbench-DS, outperforming
prior open-source deep research agents such as WebSailor-72B and DeepDive-32B.
68dcae184159d1f2418f9bd9
Gongrui Zhang
68dcae184159d1f2418f9bda
Jialiang Zhu
68dcae184159d1f2418f9bdb
Ruiqi Yang
68dcae184159d1f2418f9bdc
Kai Qiu
68dcae184159d1f2418f9bdd
Miaosen Zhang
claimed_verified
2025-10-01T10:21:07.867Z
62a30bf72dac39c2173c0a8c
/avatars/15fb1ea3dcc7ccd8bc8002ce282e27b3.svg
Miaosen Zhang
user
Miaosen
68dcae184159d1f2418f9bde
Zhirong Wu
68dcae184159d1f2418f9bdf
Qi Dai
68dcae184159d1f2418f9be0
Bei Liu
68dcae184159d1f2418f9be1
Chong Luo
68dcae184159d1f2418f9be2
Zhengyuan Yang
claimed_verified
2025-10-02T03:08:49.940Z
630713411801ecc7d2592a7c
/avatars/fb36f69f03421c3a2a7f72ba0858fa60.svg
Zhengyuan Yang
user
zyang39
68dcae184159d1f2418f9be3
Linjie Li
68dcae184159d1f2418f9be4
Lijuan Wang
68dcae184159d1f2418f9be5
Weizhu Chen
68dcae184159d1f2418f9be6
Yuan Zhang
68dcae184159d1f2418f9be7
Xin Li
68dcae184159d1f2418f9be8
Zhaoyi Liu
68dcae184159d1f2418f9be9
Xin Geng
68dcae184159d1f2418f9bea
Baining Guo
InfoAgent: Advancing Autonomous Information-Seeking Agents
Building Large Language Model agents that expand their capabilities by
interacting with external tools represents a new frontier in AI research and
applications. In this paper, we introduce InfoAgent, a deep research agent
powered by an innovative data synthesis pipeline and orchestrated web search
tools. To construct challenging, hard-to-find queries,we build entity trees and
apply sub-tree sampling with entity fuzzification to systematically increase
question difficulty. Unlike prior work that relies heavily on commercial search
tools, we develop a dedicated self-hosted search infrastructure, enhancing
transparency of agent environments and facilitating further advancement of
agent capacity. We evaluate the effectiveness of our data pipeline by measuring
the average number of tool calls required to correctly answer a question, and
also show that our agent yields better performance when equipped with our
tools. Our InfoAgent is post-trained from Qwen3-14B using a two-stage
recipe: cold-start supervised finetuning to instill long-horizon search
behaviors, followed by reinforcement learning which significantly improves
reasoning-driven tool use. With our methods, InfoAgent achieves 15.3\% accuracy
on BrowseComp, 29.2\% on BrowseComp-ZH, and 40.4\% on Xbench-DS, outperforming
prior open-source deep research agents such as WebSailor-72B and DeepDive-32B.
InfoAgent, a deep research agent using a custom data synthesis pipeline and search infrastructure, outperforms existing agents by improving tool use and reasoning.
deep research agent data synthesis pipeline entity trees sub-tree sampling entity fuzzification self-hosted search infrastructure cold-start supervised finetuning reinforcement learning BrowseComp BrowseComp-ZH Xbench-DS WebSailor-72B DeepDive-32B