In-Context Reinforcement Learning for Tool Use in Large Language Models
In-Context Reinforcement Learning for Tool Use in Large Language Models explores ICRL is a reinforcement learning framework that enables LLMs to effectively use external tools without supervised fine-tuning, offering a data-efficient alternative for tool-augmented language models.. Commercial viability score: 7/10 in LLM Tool Use.
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