most citedGrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length

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cs.AI2025

Improving Large Language Models Function Calling and Interpretability via Guided-Structured Templates

Hy Dang, Tianyi Liu, Zhuofeng Wu +9

Large language models (LLMs) have demonstrated strong reasoning and tool-use capabilities, yet they often fail in real-world tool-interactions due to incorrect parameterization, po…

cs.AI2025

RRO: LLM Agent Optimization Through Rising Reward Trajectories

Zilong Wang, Jingfeng Yang, Sreyashi Nag +5

Large language models (LLMs) have exhibited extraordinary performance in a variety of tasks while it remains challenging for them to solve complex multi-step tasks as agents. In pr…