11 papers
FS-Researcher: Test-Time Scaling for Long-Horizon Research Tasks with File-System-Based Agents
Chiwei Zhu, Benfeng Xu, Mingxuan Du +4
Deep research is emerging as a representative long-horizon task for large language model (LLM) agents. However, long trajectories in deep research often exceed model context limits…
A-RAG: Scaling Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces
Mingxuan Du, Benfeng Xu, Chiwei Zhu +4
Frontier language models have demonstrated strong reasoning and long-horizon tool-use capabilities. However, existing RAG systems fail to leverage these capabilities. They still re…
Wiki Live Challenge: Challenging Deep Research Agents with Expert-Level Wikipedia Articles
Shaohan Wang, Benfeng Xu, Licheng Zhang +5
Deep Research Agents (DRAs) have demonstrated remarkable capabilities in autonomous information retrieval and report generation, showing great potential to assist humans in complex…
DeepResearch Bench II: Diagnosing Deep Research Agents via Rubrics from Expert Report
Ruizhe Li, Mingxuan Du, Benfeng Xu +3
Deep Research Systems (DRS) aim to help users search the web, synthesize information, and deliver comprehensive investigative reports. However, how to rigorously evaluate these sys…
An Index-based Approach for Efficient and Effective Web Content Extraction
Yihan Chen, Benfeng Xu, Xiaorui Wang +1
As web agents (e.g., Deep Research) routinely consume massive volumes of web pages to gather and analyze information, LLM context management -- under large token budgets and low si…
MCP-AgentBench: Evaluating Real-World Language Agent Performance with MCP-Mediated Tools
Zikang Guo, Benfeng Xu, Chiwei Zhu +3
The Model Context Protocol (MCP) is rapidly emerging as a pivotal open standard, designed to enhance agent-tool integration and interoperability, and is positioned to unlock a new…