agentsPublished: October 27, 2023
AgentTuning: Enabling generalized agent capabilities in LLMs
By Aohan Zeng, Ming Ji, Luoxuan Weng, Xiaohan Zhang, Minlie Huang, Jie Tang
Research TL;DR
"Examines instruction-tuning methodologies optimized for agentic operations. Builds a customized instruction set to teach LLMs specialized planning and tool-use behaviors."
Abstract
We present AgentTuning, a simple and general method to enhance the agent capabilities of LLMs while preserving their general abilities. We construct AgentInstruct, a high-quality dataset, and fine-tune models to exhibit robust tool-use, planning, and self-correction behaviors.
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