diff --git a/docs/en/user_guides/datasets.md b/docs/en/user_guides/datasets.md
index cc71b1fd..22589cbf 100644
--- a/docs/en/user_guides/datasets.md
+++ b/docs/en/user_guides/datasets.md
@@ -103,7 +103,7 @@ afqmc_datasets = [
 > [!TIP]
 > Additionally, for binary evaluation metrics (such as accuracy, pass-rate, etc.), you can also set the parameter `k` in conjunction with `n` for [G-Pass@k](http://arxiv.org/abs/2412.13147) evaluation. The formula for G-Pass@k is:
 >
-> $$ G-Pass@k_\tau=\mathbb{E}_{Data}\left[ \sum_{j=\lceil \tau \cdot k \rceil}^c \frac{{c \choose j} \cdot {n - c \choose k - j}}{{n \choose k}} \right], $$ 
+> $$ \text{G-Pass@}k_\tau=E_{\text{Data}}\left[ \sum_{j=\lceil \tau \cdot k \rceil}^c \frac{{c \choose j} \cdot {n - c \choose k - j}}{{n \choose k}} \right], $$ 
 >
 > where $n$ is the number of evaluations, and $c$ is the number of times that passed or were correct out of $n$ runs. An example configuration is as follows: