diff --git a/docs/source/nnls_tutorial.rst b/docs/source/nnls_tutorial.rst
index ea70e27b5..3a2cc65eb 100644
--- a/docs/source/nnls_tutorial.rst
+++ b/docs/source/nnls_tutorial.rst
@@ -917,13 +917,11 @@ directory contains a number of other examples:
 
      /path/to/bin/pose_graph_2d /path/to/dataset/dataset.g2o
 
-  where this assumes the install directory is located in the repository.
-
   A python script is provided to visualize the resulting output files.
 
   .. code-block:: bash
 
-     /path/to/repo/robotics/slam/pose_graph_2d/plot_results.py --optimized_poses ./poses_optimized.txt --initial_poses ./poses_original.txt
+     /path/to/repo/examples/slam/pose_graph_2d/plot_results.py --optimized_poses ./poses_optimized.txt --initial_poses ./poses_original.txt
 
   As an example, a standard synthetic benchmark dataset [#f10]_ created by Edwin
   Olson which has 3500 nodes in a grid world with a total of 5598 edges was
diff --git a/examples/slam/pose_graph_2d/README.md b/examples/slam/pose_graph_2d/README.md
index ecac76409..fed51a60e 100644
--- a/examples/slam/pose_graph_2d/README.md
+++ b/examples/slam/pose_graph_2d/README.md
@@ -18,7 +18,7 @@ Running
 This package includes an executable `pose_graph_2d` that will read a problem
 definition file. This executable can work with any 2D problem definition that
 uses the g2o format. It would be relatively straightforward to implement a new
-reader for a different format such as toro or others. `pose_graph_2d` will print
+reader for a different format such as TORO or others. `pose_graph_2d` will print
 the Ceres solver full summary and then output to disk the original and optimized
 poses (`poses_original.txt` and `poses_optimized.txt`, respectively) of the
 robot in the following format:
@@ -33,16 +33,14 @@ pose_id x y yaw_radians
 where `pose_id` is the corresponding integer ID from the file definition. Note,
 the file will be sorted in ascending order for the `pose_id`.
 
-The executable `solve_pose_graph_2d` expects the first argument to be the path
-to the problem definition. To run the executable,
+The executable `pose_graph_2d` expects the first argument to be the path to the
+problem definition. To run the executable,
 
 ```
 /path/to/bin/pose_graph_2d /path/to/dataset/dataset.g2o
 ```
 
-where this assumes the install directory is located in the repository.
-
 A python script is provided to visualize the resulting output files.
 ```
-/path/to/repo/robotics/slam/pose_graph_2d/plot_results.py --optimized_poses ./poses_optimized.txt --initial_poses ./poses_original.txt
+/path/to/repo/examples/slam/pose_graph_2d/plot_results.py --optimized_poses ./poses_optimized.txt --initial_poses ./poses_original.txt
 ```
diff --git a/examples/slam/pose_graph_2d/pose_graph_2d.cc b/examples/slam/pose_graph_2d/pose_graph_2d.cc
index 031025935..e6caf7e36 100644
--- a/examples/slam/pose_graph_2d/pose_graph_2d.cc
+++ b/examples/slam/pose_graph_2d/pose_graph_2d.cc
@@ -49,7 +49,7 @@ namespace ceres {
 namespace examples {
 
 // Constructs the nonlinear least squares optimization problem from the pose
-// graph constraints and solves it.
+// graph constraints.
 void BuildOptimizationProblem(const std::vector<Constraint2d>& constraints,
                               std::map<int, Pose2d>* poses,
                               ceres::Problem* problem) {