diff --git a/units/en/unit6/variance-problem.mdx b/units/en/unit6/variance-problem.mdx
index 9ce3d8e..1fbbe9c 100644
--- a/units/en/unit6/variance-problem.mdx
+++ b/units/en/unit6/variance-problem.mdx
@@ -27,4 +27,5 @@ However, increasing the batch size significantly **reduces sample efficiency**.
 If you want to dive deeper into the question of variance and bias tradeoff in Deep Reinforcement Learning, you can check out these two articles:
 - [Making Sense of the Bias / Variance Trade-off in (Deep) Reinforcement Learning](https://blog.mlreview.com/making-sense-of-the-bias-variance-trade-off-in-deep-reinforcement-learning-79cf1e83d565)
 - [Bias-variance Tradeoff in Reinforcement Learning](https://www.endtoend.ai/blog/bias-variance-tradeoff-in-reinforcement-learning/)
+- [High Variance in Policy gradients](https://balajiai.github.io/high_variance_in_policy_gradients)
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