MLLM-CL Benchmark Description
MLLM-CL is a novel benchmark encompassing domain and ability continual learning, where the former focuses on independently and identically distributed (IID) evaluation across evolving mainstream domains, whereas the latter evaluates on non-IID scenarios with emerging model ability. For more details, please refer to:
MLLM-CL: Continual Learning for Multimodal Large Language Models [paper], [code].
Hongbo Zhao, Fei Zhu, Haiyang Guo, Meng Wang, Rundong Wang, Gaofeng Meng, Zhaoxiang Zhang
Usage
This repo is used to open-source MR-LoRA's router LoRA, including 4 branches.
Citation
@article{zhao2025mllm,
title={MLLM-CL: Continual Learning for Multimodal Large Language Models},
author={Zhao, Hongbo and Zhu, Fei and Guo, Haiyang and Wang, Meng and Wang, Rundong and Meng, Gaofeng and Zhang, Zhaoxiang},
journal={arXiv preprint arXiv:2506.05453},
year={2025}
}
Contact
Please post an issue on our GitHub.
About us: MLLM-CL Community
We are the members from MLLM-CL, an open-source community focused on Continual learning of Multimodal Large Language Models. If you are interested in our community, feel free to contact us on GitHub or by email.
Model tree for MLLM-CL/MRLoRA_Router
Base model
OpenGVLab/InternVL-Chat-ViT-6B-Vicuna-7B