diff --git a/src/TNL/Matrices/SparseMatrix.hpp b/src/TNL/Matrices/SparseMatrix.hpp
index 60f4695f05ae429a1e473ad50786b56db3655ff2..992443434628ee9f058095ed53b3a7151aa34b78 100644
--- a/src/TNL/Matrices/SparseMatrix.hpp
+++ b/src/TNL/Matrices/SparseMatrix.hpp
@@ -590,7 +590,8 @@ operator=( const Dense< Real_, Device_, Index_, RowMajorOrder, RealAllocator_ >&
          {
             IndexType thisGlobalIdx = segments_view.getGlobalIndex( rowIdx, rowLocalIndexes_view[ rowIdx ]++ );
             columns_view[ thisGlobalIdx ] = columnIdx;
-            values_view[ thisGlobalIdx ] = value;
+            if( ! isBinary() )
+               values_view[ thisGlobalIdx ] = value;
          }
       };
       matrix.forAllRows( f );
@@ -700,7 +701,8 @@ operator=( const RHSMatrix& matrix )
          {
             IndexType thisGlobalIdx = segments_view.getGlobalIndex( rowIdx, localIdx++ );
             columns_view[ thisGlobalIdx ] = columnIndex;
-            values_view[ thisGlobalIdx ] = value;
+            if( ! isBinary() )
+               values_view[ thisGlobalIdx ] = value;
             rowLocalIndexes_view[ rowIdx ] = localIdx;
          }
       };
diff --git a/src/UnitTests/Matrices/BinarySparseMatrixCopyTest.h b/src/UnitTests/Matrices/BinarySparseMatrixCopyTest.h
index d8fefeed79b50a8dc0123eeae6d125d9f28fb227..b901acbbd93dd7a7416645e70441d1382bd381a3 100644
--- a/src/UnitTests/Matrices/BinarySparseMatrixCopyTest.h
+++ b/src/UnitTests/Matrices/BinarySparseMatrixCopyTest.h
@@ -440,7 +440,7 @@ void tridiagonalMatrixAssignment()
    TridiagonalHost hostMatrix( rows, columns );
    for( IndexType i = 0; i < rows; i++ )
       for( IndexType j = TNL::max( 0, i - 1 ); j < TNL::min( columns, i + 2 ); j++ )
-         hostMatrix.setElement( i, j, 1 );
+         hostMatrix.setElement( i, j, TNL::min( i + j, 1 ) );
 
    Matrix matrix;
    matrix = hostMatrix;
@@ -456,7 +456,7 @@ void tridiagonalMatrixAssignment()
          if( abs( i - j ) > 1 )
             EXPECT_EQ( matrix.getElement( i, j ), 0.0 );
          else
-            EXPECT_EQ( matrix.getElement( i, j ), 1.0 );
+            EXPECT_EQ( matrix.getElement( i, j ), TNL::min( i + j, 1 ) );
       }
 
 #ifdef HAVE_CUDA
@@ -471,7 +471,7 @@ void tridiagonalMatrixAssignment()
          if( abs( i - j ) > 1 )
             EXPECT_EQ( matrix.getElement( i, j ), 0.0 );
          else
-            EXPECT_EQ( matrix.getElement( i, j ), 1.0 );
+            EXPECT_EQ( matrix.getElement( i, j ), TNL::min( i + j, 1 ) );
       }
 #endif
 }
@@ -493,7 +493,7 @@ void multidiagonalMatrixAssignment()
    for( IndexType i = 0; i < rows; i++ )
       for( IndexType j = 0; j < columns; j++ )
          if( diagonals.containsValue( j - i ) )
-            hostMatrix.setElement( i, j, 1 );
+            hostMatrix.setElement( i, j, TNL::min( i + j, 1 ) );
 
    Matrix matrix;
    matrix = hostMatrix;
@@ -510,7 +510,7 @@ void multidiagonalMatrixAssignment()
       for( IndexType j = 0; j < columns; j++ )
       {
          if( diagonals.containsValue( j - i ) )
-            EXPECT_EQ( matrix.getElement( i, j ), 1.0 );
+            EXPECT_EQ( matrix.getElement( i, j ), TNL::min( i + j, 1 ) );
          else
             EXPECT_EQ( matrix.getElement( i, j ), 0.0 );
       }
@@ -525,7 +525,7 @@ void multidiagonalMatrixAssignment()
       for( IndexType j = 0; j < columns; j++ )
       {
          if( diagonals.containsValue( j - i ) )
-            EXPECT_EQ( matrix.getElement( i, j ), 1.0 );
+            EXPECT_EQ( matrix.getElement( i, j ), TNL::min( i + j, 1 ) );
          else
             EXPECT_EQ( matrix.getElement( i, j ), 0.0 );
       }
@@ -546,7 +546,7 @@ void denseMatrixAssignment()
    DenseHost hostMatrix( rows, columns );
    for( IndexType i = 0; i < columns; i++ )
       for( IndexType j = 0; j <= i; j++ )
-         hostMatrix( i, j ) = i + j;
+         hostMatrix( i, j ) = TNL::min( i + j, 1 );
 
    Matrix matrix;
    matrix = hostMatrix;
@@ -561,7 +561,7 @@ void denseMatrixAssignment()
          if( j > i )
             EXPECT_EQ( matrix.getElement( i, j ), 0.0 );
          else
-            EXPECT_EQ( matrix.getElement( i, j ), 1.0 );
+            EXPECT_EQ( matrix.getElement( i, j ), TNL::min( i + j, 1 ) );
       }
 
 #ifdef HAVE_CUDA
@@ -576,7 +576,7 @@ void denseMatrixAssignment()
          if( j > i )
             EXPECT_EQ( matrix.getElement( i, j ), 0.0 );
          else
-            EXPECT_EQ( matrix.getElement( i, j ), 1.0 );
+            EXPECT_EQ( matrix.getElement( i, j ), TNL::min( i + j, 1 ) );
       }
 #endif
 }