Update README.md

README.md

@@ -12,6 +12,7 @@ Difficulty scores are estimated using the Qwen 2.5-MATH-7B model with the follow
 
 - `temperature = 0.6`
 - `top_p = 0.9`
+- `max_tokens=4096`
 - Inference performed via [vLLM](https://github.com/vllm-project/vllm)
 - Each problem is attempted **128 times**
 
@@ -20,3 +21,6 @@ The difficulty score for each problem is computed as:
      d_i = 100 × (1 - (# successes / 128))
 
 This scoring approach ensures a balanced estimation: a strong model would trivially succeed on all problems, undermining difficulty measurement, while a weak model would fail uniformly, limiting the usefulness of the signal. Qwen 2.5-MATH-7B was chosen for its **mid-range capabilities**, providing **informative gradients** in problem difficulty across the dataset.
+
+## Contact
+Feel free to contact Taiwei Shi ([email protected]) if you have any questions.