LLMs Trained For Multi-Step Tool Use
Researchers have developed a new method called 'Synthesize and Reward' to train large language models for multi-step tool orchestration. This reinforcement learning approach aims to improve the models' ability to execute complex sequences of tool calls in live environments.
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Developing
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Sources · 7 independent
Modernity/arxiv
“Synthesize and Reward -- Reinforcement Learning for Multi-Step Tool Use in Live Environments. Authors: Ibrahim Abdelaziz, Asim Munawar, Kinjal Basu, Maxwell Crouse, Chulaka Gunasekara, Suneet Katrekar, Pavan Kapanipathi Abstract: Training LLMs to orchestrate multi-step tool calls is held back...”
Modernity/arxiv
“Training LLMs to orchestrate multi-step tool calls is held back...”
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