diff --git a/docs/source/conceptual/paged_attention.md b/docs/source/conceptual/paged_attention.md
index f5062767..2c9885b9 100644
--- a/docs/source/conceptual/paged_attention.md
+++ b/docs/source/conceptual/paged_attention.md
@@ -6,4 +6,4 @@ PagedAttention addresses the memory waste by partitioning the KV cache into bloc
 
 The use of a lookup table to access the memory blocks can also help with KV sharing across multiple generations. This is helpful for techniques such as _parallel sampling_, where multiple outputs are generated simultaneously for the same prompt. In this case, the cached KV blocks can be shared among the generations.
 
-You can learn more about PagedAttention by reading the documentation [here](https://vllm.ai/).
+TGI's PagedAttention implementation leverages the custom cuda kernels developed by the [vLLM Project](https://github.com/vllm-project/vllm). You can learn more about this technique in the [project's page](https://vllm.ai/).