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cs.CL2026

Search More, Think Less: Rethinking Long-Horizon Agentic Search for Efficiency and Generalization

Qianben Chen, Tianrui Qin, King Zhu +21

Recent deep research agents primarily improve performance by scaling reasoning depth, but this leads to high inference cost and latency in search-intensive scenarios. Moreover, gen…

cs.CL2026

O-Researcher: An Open Ended Deep Research Model via Multi-Agent Distillation and Agentic RL

Yi Yao, He Zhu, Piaohong Wang +12

The performance gap between closed-source and open-source large language models (LLMs) is largely attributed to disparities in access to high-quality training data. To bridge this…

cs.CL2025

AFM: An Adaptive Agent Foundation Model for Tool-Aware Hybrid Reasoning

Qianben Chen, Jingyi Cao, Jiayu Zhang +12

Large language models split into two families: reasoning-centric LLMs, which strengthen internal chain-of-thought reasoning but cannot invoke external tools, and agentic LLMs, whic…

cs.CL2025

ACADREASON: Exploring the Limits of Reasoning Models with Academic Research Problems

Xin Gui, King Zhu, JinCheng Ren +17

In recent years, the research focus of large language models (LLMs) and agents has shifted increasingly from demonstrating novel capabilities to complex reasoning and tackling chal…

cs.CL2025

TaskCraft: Automated Generation of Agentic Tasks

Dingfeng Shi, Jingyi Cao, Qianben Chen +14

Agentic tasks, which require multi-step problem solving with autonomy, tool use, and adaptive reasoning, are becoming increasingly central to the advancement of NLP and AI. However…