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arXiv · 2311.05437

LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents

Shilong Liu·Hao Cheng·Haotian Liu·Hao Zhang·Feng Li·Tianhe Ren·Xueyan Zou·Jianwei Yang·Hang Su·Jun Zhu·Lei Zhang·Jianfeng Gao·Chunyuan Li
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Abstract

LLaVA-Plus is a general-purpose multimodal assistant that expands the capabilities of large multimodal models. It maintains a skill repository of pre-trained vision and vision-language models and can activate relevant tools based on users' inputs to fulfill real-world tasks. LLaVA-Plus is trained on multimodal instruction-following data to acquire the ability to use tools, covering visual understanding, generation, external knowledge retrieval, and compositions. Empirical results show that LLaVA-Plus outperforms LLaVA in existing capabilities and exhibits new ones. It is distinct in that the image query is directly grounded and actively engaged throughout the entire human-AI interaction sessions, significantly improving tool use performance and enabling new scenarios.

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Shilong Liu, Hao Cheng, Haotian Liu, Hao Zhang, Feng Li, Tianhe Ren, Xueyan Zou, Jianwei Yang, Hang Su, Jun Zhu, Lei Zhang, Jianfeng Gao, Chunyuan Li. 2023-11-09. LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents. https://arxiv.org/abs/2311.05437

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