Looking for Case Studies on Using RL PPO/GRPO to Improve Tool Utilization Accuracy in LLM-based Agents

Hi everyone,

I’m currently working on LLM agent development and am exploring how Reinforcement Learning (RL), specifically PPO or GRPO, can be used to enhance tool utilization accuracy within these agents.

I have a few specific questions:

1. What type of base model is typically used for training? Is it a base LLM or an SFT instruction-following model?
2. What training data is suitable for fine-tuning, and are there any sample datasets available?
3. Which RL algorithms are most commonly used in these applications—PPO or GRPO?
4. Are there any notable frameworks, such as VERL or TRL, used in these types of RL applications?

I’d appreciate any case studies, insights, or advice from those who have worked on similar projects.

Thanks in advance!