README.md

---
license: mit
task_categories:
- token-classification
language:
- en
tags:
- TAM
- CAM
- MLLM
- VLLM
- Explainability
pretty_name: TAM
size_categories:
- 1B<n<10B
---

# Token Activation Map to Visually Explain Multimodal LLMs
We introduce the Token Activation Map (TAM), a groundbreaking method that cuts through the contextual noise in Multimodal LLMs. This technique produces exceptionally clear and reliable visualizations, revealing the precise visual evidence behind every word the model generates.

# Evaluation Datasets
This is a dataset repo to evaluate TAM. The involved datasets are formatted for easy useage.

# Paper and Code
[![arXiv](https://img.shields.io/badge/arXiv-2506.23270-brown?logo=arxiv&style=flat-square)](https://arxiv.org/abs/2506.23270)

[🐙 GitHub Page](https://github.com/xmed-lab/TAM)

## Citation
```
@misc{li2025tokenactivationmapvisually,
      title={Token Activation Map to Visually Explain Multimodal LLMs}, 
      author={Yi Li and Hualiang Wang and Xinpeng Ding and Haonan Wang and Xiaomeng Li},
      year={2025},
      eprint={2506.23270},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2506.23270}, 
}
```