Author

Ting-Yao Hu

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#machine learning Preprint Oct 2026

Structuring MoE Expert Selection for Agentic Reinforcement Learning

Long-horizon LLM agents are frequently implemented using sparse mixture-of-experts (MoE) models, yet the co-design of agentic behavior and MoE structures remains underexplored. In this work, we comprehensively study the connections between agentic post-training and MoE expert selection. In off-the-shelf MoE models, we...

Bo-Lian Li, Ting-Yao Hu, Cheng-Yu Hsieh et al. · 0 citations

Jul 2026

Environment-free Synthetic Data Generation for API-Calling Agents

Training API-calling large language model (LLM) agents demands massive amounts of high-quality trajectories. However, collecting such data at scale typically requires fully implemented environments with executable APIs and realistic, pre-populated backend databases, creating a major bottleneck for scalability. To overc...

Seanie Lee, Sanjoy Chowdhury, Chao Jiang et al. · arXiv.org · 2 citations