Update README.md

README.md

@@ -46,4 +46,34 @@ quantization + INT8 GEMM, rescaled by `scale_x * scale_w`. No whole-weight dequa
 - BF16 vs INT8 generation (same seed/settings): identical patch counts (200/200), finite latents, EN/ZH ASR-verified, speaker-similarity parity (0.9007 vs 0.8991)
 - Peak VRAM 13.1 -> 8.3 GiB; generation ~1.3x slower (memory optimization, honestly reported)
 
+## Usage Disclaimer
+
+- The project incorporates zero-shot voice cloning functionality; Please note that this capability is intended **solely for academic research purposes**.
+- **DO NOT** use this model for **ANY illegal activities**❗️❗️
+- The developers assume no liability for any misuse of this model.
+- If you identify any instances of **abuse**, **misuse**, or **fraudulent** activities related to this project, **please report them to our team immediately.**
+
+
+## Citation
+
+```bib
+@article{fireredtts3,
+  title   = {FireRedTTS3: Unified Speech Generation and Editing with Semantically Enriched Speech Representations},
+  author  = {FireRed Team},
+  journal = {arXiv preprint},
+  year    = {2026},
+}
+```
+
+
+## Acknowledgements
+
+- [Qwen3](https://github.com/QwenLM/Qwen3) and [Qwen2-Audio](https://github.com/QwenLM/Qwen2-Audio) for the language model and audio understanding foundations
+- [DiTAR](https://arxiv.org/abs/2502.03930) for the patch-level diffusion autoregressive formulation
+- [X-Codec](https://github.com/zhenye234/xcodec) for the discriminator design used in RedAE training
+- [CAM++](https://modelscope.cn/models/iic/speech_campplus_sv_en_voxceleb_16k) for speaker embedding extraction
+- [fastText](https://fasttext.cc/docs/en/language-identification.html) for automatic language identification
+- [WeTextProcessing](https://github.com/wenet-e2e/WeTextProcessing) (wetext) for the Chinese / English text normalization front-end
+
+
 All credit to the FireRed Team — see the upstream repo and model card. Apache-2.0.