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cs.CL2026
RE-TRAC: REcursive TRAjectory Compression for Deep Search Agents
Jialiang Zhu, Gongrui Zhang, Xiaolong Ma +17
LLM-based deep research agents are largely built on the ReAct framework. This linear design makes it difficult to revisit earlier states, branch into alternative search directions,…
cs.CL2025
InfoAgent: Advancing Autonomous Information-Seeking Agents
Gongrui Zhang, Jialiang Zhu, Ruiqi Yang +15
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…
cs.CL2025★ 3 cited
Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning
Tian Xie, Zitian Gao, Qingnan Ren +7
Inspired by the success of DeepSeek-R1, we explore the potential of rule-based reinforcement learning (RL) in large reasoning models. To analyze reasoning dynamics, we use syntheti…