diff --git a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
index 8150737..784637a 100644
--- a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
@@ -131,7 +131,7 @@
      *                     If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions.
      *                     If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension.
      *                     Data type supported: Same as @p input.
-     * @param[in]  biases  Bias tensor. Can be nullptr. Data type supported:Same as @p input.
+     * @param[in]  biases  Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8.
      * @param[out] output  Destination tensor. Its shape should be equal to the output of a matrix multiplication between:
      *                     - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer
      *                     - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer.
@@ -142,17 +142,17 @@
                    FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
     /** Static function to check if given info will lead to a valid configuration of @ref NEFullyConnectedLayer
      *
-     * @param[in]  input   Source tensor info. Data type supported: QASYMM8/F16/F32.
-     * @param[in]  weights Weights tensor info. The weights must be 2 dimensional.
-     *                     If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions.
-     *                     If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension.
-     *                     Data type supported: Same as @p input.
-     * @param[in]  biases  Bias tensor info. Can be nullptr. Data type supported:Same as @p input.
-     * @param[out] output  Destination tensor info. Its shape should be equal to the output of a matrix multiplication between:
-     *                     - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer
-     *                     - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer.
-     *                     Data type supported: Same as @p input.
-     * @param[in]  fc_info (Optional) Fully connected layer additional info
+     * @param[in] input   Source tensor info. Data type supported: QASYMM8/F16/F32.
+     * @param[in] weights Weights tensor info. The weights must be 2 dimensional.
+     *                    If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions.
+     *                    If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension.
+     *                    Data type supported: Same as @p input.
+     * @param[in] biases  Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8.
+     * @param[in] output  Destination tensor info. Its shape should be equal to the output of a matrix multiplication between:
+     *                    - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer
+     *                    - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer.
+     *                    Data type supported: Same as @p input.
+     * @param[in] fc_info (Optional) Fully connected layer additional info
      *
      * @return a status
      */
diff --git a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h
index 665d4f1..660f559 100644
--- a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h
@@ -64,15 +64,17 @@
     /** Set the input and output tensors.
      *
      * @param[in]  weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32.
-     * @param[in]  biases  Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
+     * @param[in]  biases  Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
+     *                     Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED.
      * @param[out] output  Destination tensor. Data types supported: Same as @p weights.
      */
     void configure(const ITensor *weights, const ITensor *biases, ITensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref NEConvolutionLayerReshapeWeights
      *
      * @param[in] weights Weights tensor info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32.
-     * @param[in] biases  Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
-     * @param[in] output  Destination tensor info. Data types supported: Same as @p weights.
+     * @param[in] biases  Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
+     *                    Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED.
+     * @param[in] output  Destination tensor. Data types supported: Same as @p weights.
      *
      * @return an error status
      */