| <div align="center"> | |
| <h1 style="font-size: 32px; font-weight: bold;"> A Single Layer to Explain Them All: Understanding Massive Values in Large Language Models </h1> | |
| <br> | |
| <br> | |
| <a href=""> | |
| <img src="https://img.shields.io/badge/ArXiv-WeMask-brown?logo=arxiv" alt="Paper"> | |
| </a> | |
| <a href="https://huggingface.co/DarkBluee/WeMask"> | |
| <img src="https://img.shields.io/badge/🤗 huggingface-Model-purple" alt="checkpoint"> | |
| </a> | |
| <a href="https://vanpe20.github.io/ME-Layer.github.io/"> | |
| <img src="https://img.shields.io/badge/-HomePage-black?logo=github" alt="checkpoint"> | |
| </a> | |
| </div> | |
| </div> | |
| ## Start | |
| This page is the model of WeMask, the github link is [ME-Layer](https://github.com/vanpe20/ME_Layer). We use [Qwen-3-VL-4B](https://huggingface.co/Qwen/Qwen3-4B) as our foundation model for SFT and RL training. You can follow the guideline in this repo to start testing and training. | |
| ## Citation | |
| If you think our research is helpful, please cite with | |
| ```bibtex | |
| @article{me_layer_2026, | |
| title={A Single Layer to Explain Them All: Understanding Massive Values in Large Language Models}, | |
| author={Your Name and Co-authors}, | |
| journal={Proceedings of the 43rd International Conference on Machine Learning (ICML)}, | |
| year={2026} | |
| } | |
| ``` | |