Author

Xiaoqiang Lin

2 papers indexed here

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Preprint Aug 2026

MCP-Universe RL: A Framework for Training MCP Tool-Use Agents via Reinforcement Learning

This work trains software-engineering, deep-research, and general tool-use agents on gpt-oss-20b and improves task reward in all three and presents MCP-Universe RL (MCP-U RL), an open-source framework that takes over both.

Ziyang Luo, Yan Yang, Xiang-Ru Jian et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Scaling Near-Optimal SFT-RL Annotation Budget Allocation from Small to Large LLMs

This work describes the near-optimal region, the set of allocations within a specified tolerance of peak performance, which is wide even for small tolerances, widens with model scale, and transfers reliably from small proxy models to large target models.

Jingtan Wang, A. Verma, Xiaoqiang Lin et al. · 0 citations