most citedWebWeaver: Structuring Web-Scale Evidence with Dynamic Outlines for Open-Ended Deep Research

1 citations · 2 across the 12 of their papers we have counts for

collaborators

30 papers

cs.AI2025

IterResearch: Rethinking Long-Horizon Agents with Interaction Scaling

Guoxin Chen, Zile Qiao, Xuanzhong Chen +13

Recent advances in deep-research agents have shown promise for autonomous knowledge construction through dynamic reasoning over external sources. However, existing approaches rely…

cs.CL2025

AgentFold: Long-Horizon Web Agents with Proactive Context Management

Rui Ye, Zhongwang Zhang, Kuan Li +12

LLM-based web agents show immense promise for information seeking, yet their effectiveness on long-horizon tasks is hindered by a fundamental trade-off in context management. Preva…

cs.CL2025

AgentFrontier: Expanding the Capability Frontier of LLM Agents with ZPD-Guided Data Synthesis

Xuanzhong Chen, Zile Qiao, Guoxin Chen +7

Training large language model agents on tasks at the frontier of their capabilities is key to unlocking advanced reasoning. We introduce a data synthesis approach inspired by the e…

cs.CL2025

BrowseConf: Confidence-Guided Test-Time Scaling for Web Agents

Litu Ou, Kuan Li, Huifeng Yin +8

Confidence in LLMs is a useful indicator of model uncertainty and answer reliability. Existing work mainly focused on single-turn scenarios, while research on confidence in complex…

cs.CL20251 cited

WebWeaver: Structuring Web-Scale Evidence with Dynamic Outlines for Open-Ended Deep Research

Zijian Li, Xin Guan, Bo Zhang +9

This paper tackles \textbf{open-ended deep research (OEDR)}, a complex challenge where AI agents must synthesize vast web-scale information into insightful reports. Current approac…

cs.CL2025

Demystifying deep search: a holistic evaluation with hint-free multi-hop questions and factorised metrics

Maojia Song, Renhang Liu, Xinyu Wang +6

RAG (Retrieval-Augmented Generation) systems and web agents are increasingly evaluated on multi-hop deep search tasks, yet current practice suffers from two major limitations. Firs…