Update README.md

README.md

@@ -1,3 +1,40 @@
----
-license: mit
----
+---
+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}, 
+}
+```