MIMIR: A Streamlined Platform for Personalized Agent Tuning in Domain Expertise

• URL: http://arxiv.org/abs/2404.04285v1
• Date: Wed, 3 Apr 2024 23:42:38 GMT
• Title: MIMIR: A Streamlined Platform for Personalized Agent Tuning in Domain Expertise
• Authors: Chunyuan Deng, Xiangru Tang, Yilun Zhao, Hanming Wang, Haoran Wang, Wangchunshu Zhou, Arman Cohan, Mark Gerstein,
• Abstract summary: textscMimir is a streamlined platform offering a customizable pipeline for personalized agent tuning. textscMimir supports the generation of general instruction-tuning datasets from the same input. textscMimir integrates these features into a cohesive end-to-end platform, facilitating everything from the uploading of personalized files to one-click agent fine-tuning.
• Score: 49.83486066403154
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recently, large language models (LLMs) have evolved into interactive agents, proficient in planning, tool use, and task execution across a wide variety of tasks. However, without specific agent tuning, open-source models like LLaMA currently struggle to match the efficiency of GPT- 4, particularly given the scarcity of agent-tuning datasets for fine-tuning. In response, we introduce \textsc{Mimir}: a streamlined platform offering a customizable pipeline that enables users to leverage both private knowledge and publicly available, legally compliant datasets at scale for \textbf{personalized agent tuning}. Additionally, \textsc{Mimir} supports the generation of general instruction-tuning datasets from the same input. This dual capability ensures that language agents developed through the platform possess both specific agent abilities and general competencies. \textsc{Mimir} integrates these features into a cohesive end-to-end platform, facilitating everything from the uploading of personalized files to one-click agent fine-tuning.

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