Exploring Next
Exploring Next — Ep 219 w/ Justy & Cody — In-Context Reinforcement Learning for Tool Use in Large Language Models
Episode 219 explores In-Context Reinforcement Learning (ICRL), a breakthrough approach that teaches language models to use external tools without expensive supervised fine-tuning. Instead of requiring thousands of labeled examples upfront, ICRL uses few-shot prompting during reinforcement learning training, gradually reducing examples until the model masters tool use independently.