Add model card and pipeline tag

README.md

@@ -1,3 +1,30 @@
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-license: cc-by-4.0
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+---
+license: cc-by-4.0
+pipeline_tag: audio-text-to-text
+---
+
+# MATS: An Audio Language Model under Text-only Supervision
+
+MATS is an audio-language multimodal Large Language Model (LLM) designed to handle multiple audio tasks using solely text-only supervision. By leveraging pre-trained audio-language alignment models such as CLAP, MATS projects the shared audio-language latent space into the LLM latent space, enabling audio comprehension without relying on audio data during training.
+
+- **Paper:** [MATS: An Audio Language Model under Text-only Supervision](https://huggingface.co/papers/2502.13433)
+- **GitHub Repository:** [https://github.com/wangwen-banban/MATS](https://github.com/wangwen-banban/MATS)
+
+## Highlights
+
+- **Text-only Supervision:** Endows LLMs with audio comprehension capabilities without using audio data for fine-tuning.
+- **Santa Mechanism:** Bridges the modality gap between audio and language embeddings within CLAP (Strongly-related noisy text with audio).
+- **Versatility:** Capable of handling various audio tasks including captioning, classification, and Question Answering.
+
+## Citation
+
+If you find MATS useful in your research, please cite:
+
+```bibtex
+@article{wang2025matsaudiolanguagemodel,
+  title={MATS: An Audio Language Model under Text-only Supervision},
+  author={Wen Wang and Ruibing Hou and Hong Chang and Shiguang Shan and Xilin Chen},
+  journal={arXiv preprint arXiv:2502.13433},
+  year={2025}
+}
+```