README.md

---
license: apache-2.0
language:
- en
metrics:
- accuracy
base_model:
- llava-hf/llava-1.5-7b-hf
- OpenGVLab/InternVL-Chat-ViT-6B-Vicuna-7B
base_model_relation: adapter
tags:
- router
- MLLM-CL
- llava
- internvl
- MR-LoRA
pipeline_tag: visual-question-answering
library_name: transformers
datasets:
- MLLM-CL/MLLM-CL-ReplayData
---
## 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](https://arxiv.org/abs/2506.05453)], [[code](https://github.com/bjzhb666/MLLM-CL/)].
![](MLLM-CL.png "Magic Gardens")
[‪Hongbo Zhao](https://scholar.google.com/citations?user=Gs22F0UAAAAJ&hl=zh-CN), [Fei Zhu](https://impression2805.github.io/), [Haiyang Guo](https://ghy0501.github.io/guohaiyang0501.github.io/), [Meng Wang](https://moenupa.github.io/), Rundong Wang, [‪Gaofeng Meng](https://scholar.google.com/citations?hl=zh-CN&user=5hti_r0AAAAJ), [‪Zhaoxiang Zhang‬](https://scholar.google.com/citations?hl=zh-CN&user=qxWfV6cAAAAJ)

## 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.