ToolRL

Rudrite Research published a comparison of three approaches for teaching language models to use tools: ReAct, Toolformer, and ToolRL. The analysis contrasts prompting loops, data filtering based on mo…

Researchers Qian et al. introduced ToolRL, a reinforcement learning method for tool use that uses a decomposed reward function—format plus correctness—outperforming supervised fine-tuning imitation. A…