diff --git a/gtsam/nonlinear/GncParams.h b/gtsam/nonlinear/GncParams.h
index 10ac80663..b1237b790 100644
--- a/gtsam/nonlinear/GncParams.h
+++ b/gtsam/nonlinear/GncParams.h
@@ -73,13 +73,12 @@ class GncParams {
   double weightsTol = 1e-4;  ///< If the weights are within weightsTol from being binary, stop iterating (only for TLS)
   Verbosity verbosity = SILENT;  ///< Verbosity level
 
-  //TODO(Varun) replace IndexVector with vector<size_t> once pybind11/stl.h is globally enabled.
-  /// Use IndexVector for inliers and outliers since it is fast + wrapping
+  /// Use IndexVector for inliers and outliers since it is fast
   using IndexVector = FastVector<uint64_t>;
   ///< Slots in the factor graph corresponding to measurements that we know are inliers
-  IndexVector knownInliers = IndexVector();
+  IndexVector knownInliers;
   ///< Slots in the factor graph corresponding to measurements that we know are outliers
-  IndexVector knownOutliers = IndexVector();
+  IndexVector knownOutliers;
 
   /// Set the robust loss function to be used in GNC (chosen among the ones in GncLossType).
   void setLossType(const GncLossType type) {
diff --git a/tests/testGncOptimizer.cpp b/tests/testGncOptimizer.cpp
index 5424a5744..4e0ebf516 100644
--- a/tests/testGncOptimizer.cpp
+++ b/tests/testGncOptimizer.cpp
@@ -750,7 +750,8 @@ TEST(GncOptimizer, optimizeSmallPoseGraph) {
   // add a few outliers
   SharedDiagonal betweenNoise = noiseModel::Diagonal::Sigmas(
       Vector3(0.1, 0.1, 0.01));
-  graph->push_back(BetweenFactor<Pose2>(90, 50, Pose2(), betweenNoise));  // some arbitrary and incorrect between factor
+  // some arbitrary and incorrect between factor
+  graph->push_back(BetweenFactor<Pose2>(90, 50, Pose2(), betweenNoise));
 
   /// get expected values by optimizing outlier-free graph
   Values expectedWithOutliers = LevenbergMarquardtOptimizer(*graph, *initial)
@@ -759,9 +760,9 @@ TEST(GncOptimizer, optimizeSmallPoseGraph) {
   // CHECK(assert_equal(expected, expectedWithOutliers, 1e-3));
 
   // GNC
-  // Note: in difficult instances, we set the odometry measurements to be
-  // inliers, but this problem is simple enought to succeed even without that
-  // assumption GncParams<GaussNewtonParams>::IndexVector knownInliers;
+  // NOTE: in difficult instances, we set the odometry measurements to be
+  // inliers, but this problem is simple enough to succeed even without that
+  // assumption.
   GncParams<GaussNewtonParams> gncParams;
   auto gnc = GncOptimizer<GncParams<GaussNewtonParams>>(*graph, *initial,
                                                         gncParams);