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README.md

@@ -6,6 +6,8 @@ license: apache-2.0
 
 Custom generate function for fuzzy speculative decoding with support for KL divergence, Jensen-Shannon divergence, and draft token-based acceptance criteria. This implementation extends the standard speculative decoding algorithm with additional divergence metrics for more flexible candidate acceptance.
 
+This implementation is based on the paper **"Fuzzy Speculative Decoding for a Tunable Accuracy-Runtime Tradeoff"** (ACL Findings 2025). See the [References](#citation) section below for full citation details.
+
 ## Features
 
 - **Fuzzy Speculative Decoding (FSD)**: Accepts candidate tokens based on distribution divergence thresholds
@@ -81,6 +83,24 @@ print(generated_text)
 - `transformers>=4.40.0`
 - `scikit-learn` (optional, for confidence threshold features)
 
+## Citation
+
+If you use this code in your research, please cite the original paper:
+
+```bibtex
+@article{holsman2025fuzzy,
+  title={Fuzzy Speculative Decoding for a Tunable Accuracy-Runtime Tradeoff},
+  author={Holsman, Maximilian and Huang, Yukun and Dhingra, Bhuwan},
+  journal={ACL Findings},
+  year={2025},
+  url={https://arxiv.org/abs/2502.20704}
+}
+```
+
+**Paper**: [Fuzzy Speculative Decoding for a Tunable Accuracy-Runtime Tradeoff](https://arxiv.org/abs/2502.20704)  
+**Authors**: Maximilian Holsman, Yukun Huang, Bhuwan Dhingra  
+**Venue**: ACL Findings 2025
+
 ## License
 
 Apache 2.0