diff --git a/docs/cugraph/source/nx_cugraph/benchmarks.md b/docs/cugraph/source/nx_cugraph/benchmarks.md
index 45085c133a9..9e0718159fa 100644
--- a/docs/cugraph/source/nx_cugraph/benchmarks.md
+++ b/docs/cugraph/source/nx_cugraph/benchmarks.md
@@ -9,7 +9,7 @@ We ran several commonly used graph algorithms on both `networkx` and `nx-cugraph
 ![bench-image](../_static/bc_benchmark.png)
 
 <figcaption style="text-align: center;">Results from running this <a
-href="https://github.com/rapidsai/cugraph/blob/HEAD/benchmarks/nx-cugraph/pytest-based/bench_algos.py">Benchmark</a><span
+href="https://github.com/rapidsai/nx-cugraph/blob/HEAD/benchmarks/nx-cugraph/pytest-based/bench_algos.py">Benchmark</a><span
 class="title-ref"></span></figcaption>
 </figure>
 
@@ -23,4 +23,4 @@ Below are the steps to reproduce the results on your own.
 
 4. Install the latest `nx-cugraph` by following the [Installation Guide](installation.md)
 
-5. Follow the instructions written in the README [here](https://github.com/rapidsai/cugraph/blob/HEAD/benchmarks/nx-cugraph/pytest-based)
+5. Follow the instructions written in the README [here](https://github.com/rapidsai/nx-cugraph/blob/HEAD/benchmarks/nx-cugraph/pytest-based/README.md)
diff --git a/docs/cugraph/source/nx_cugraph/how-it-works.md b/docs/cugraph/source/nx_cugraph/how-it-works.md
index 5696688d1b5..88788f3c0cc 100644
--- a/docs/cugraph/source/nx_cugraph/how-it-works.md
+++ b/docs/cugraph/source/nx_cugraph/how-it-works.md
@@ -110,4 +110,4 @@ This run will be much faster, typically around 5 seconds depending on your GPU.
 
 ---
 
-The latest list of algorithms supported by `nx-cugraph` can be found in [GitHub](https://github.com/rapidsai/cugraph/blob/HEAD/python/nx-cugraph/README.md#algorithms), or in the [Supported Algorithms Section](supported-algorithms.md).
+The latest list of algorithms supported by `nx-cugraph` can be found in [GitHub](https://github.com/rapidsai/nx-cugraph/blob/HEAD/README.md#supported-algorithms), or in the [Supported Algorithms Section](supported-algorithms.md).
diff --git a/docs/cugraph/source/nx_cugraph/index.rst b/docs/cugraph/source/nx_cugraph/index.rst
index 730958a5b73..1b851f968a3 100644
--- a/docs/cugraph/source/nx_cugraph/index.rst
+++ b/docs/cugraph/source/nx_cugraph/index.rst
@@ -3,7 +3,7 @@ nx-cugraph
 
 ``nx-cugraph`` is a NetworkX backend that provides **GPU acceleration** to many popular NetworkX algorithms.
 
-By simply `installing and enabling nx-cugraph <https://github.com/rapidsai/cugraph/blob/HEAD/python/nx-cugraph/README.md#install>`_, users can see significant speedup on workflows where performance is hindered by the default NetworkX implementation.
+By simply `installing and enabling nx-cugraph <https://github.com/rapidsai/nx-cugraph/blob/HEAD/README.md#installation>`_, users can see significant speedup on workflows where performance is hindered by the default NetworkX implementation.
 
 Users can have GPU-based, large-scale performance **without** changing their familiar and easy-to-use NetworkX code.
 
diff --git a/docs/cugraph/source/nx_cugraph/supported-algorithms.rst b/docs/cugraph/source/nx_cugraph/supported-algorithms.rst
index 8f57c02b240..ae32bc330fe 100644
--- a/docs/cugraph/source/nx_cugraph/supported-algorithms.rst
+++ b/docs/cugraph/source/nx_cugraph/supported-algorithms.rst
@@ -352,4 +352,4 @@ Generators
 
 
 To request nx-cugraph backend support for a NetworkX API that is not listed
-above, visit the `cuGraph GitHub repo <https://github.com/rapidsai/cugraph>`_.
+above, visit the `nx-cugraph GitHub repo <https://github.com/rapidsai/nx-cugraph>`_.