English

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

Computer Vision and Pattern Recognition 2023-11-10 v1 Artificial Intelligence Computation and Language Machine Learning Multimedia

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.

Keywords

Cite

@article{arxiv.2311.05437,
  title  = {LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents},
  author = {Shilong Liu and Hao Cheng and Haotian Liu and Hao Zhang and Feng Li and Tianhe Ren and Xueyan Zou and Jianwei Yang and Hang Su and Jun Zhu and Lei Zhang and Jianfeng Gao and Chunyuan Li},
  journal= {arXiv preprint arXiv:2311.05437},
  year   = {2023}
}

Comments

25 pages, 25M file size. Project Page: https://llava-vl.github.io/llava-plus/

R2 v1 2026-06-28T13:16:20.340Z