diff --git a/current.txt b/current.txt
index 3806cff..8ab1932 100644
--- a/current.txt
+++ b/current.txt
@@ -578,7 +578,7 @@
 5f6d3097ba84cb63c430787123f4de1b31c11f90b531b98eae9a8623a5ae962a android.hardware.neuralnetworks@1.1::types
 fb382e986c10b8fbb797a8546e8f9ea6d1107bfe6f3fb7e57f6bbbf1f807a906 android.hardware.neuralnetworks@1.2::IDevice
 40e71cd693de5b832325c5d8f081f2ff20a7ba2b89d401cee5b4b3eb0e241681 android.hardware.neuralnetworks@1.2::IPreparedModel
-6c29d6fdd5445911df5456b3b84b949cdd59fca0c0b5507662f26a5cac0cf5e5 android.hardware.neuralnetworks@1.2::types
+00649d29680f2c47edf60000c3ae7ae906ba638f0616947147e3676a83cf36fa android.hardware.neuralnetworks@1.2::types
 a785a57447a81e9c130eef6904c3a5c256076c6a04588c40620ebd6fa2660d77 android.hardware.radio@1.2::types
 1a6e2bd289f22931c526b21916910f1d4c436b7acb9556e4243de4ce8e6cc2e4 android.hardware.soundtrigger@2.0::ISoundTriggerHwCallback
 fd65298e1e09e0e3c781ab18305920d757dbe55a3b459ce17814ec5cf6dfee99 android.hardware.wifi@1.0::IWifiP2pIface
@@ -630,7 +630,7 @@
 2fa3679ad7c94b5e88724adcd560c561041068a4ca565c63830e68101988746a android.hardware.neuralnetworks@1.3::IFencedExecutionCallback
 43088ffc71945b463a7279262cfe2e290f6ed2f15d3fd6032798a3be299fb08f android.hardware.neuralnetworks@1.3::IPreparedModel
 0439a1fbbec7f16e5e4c653d85ac685d51bfafbae15b8f8cca530acdd7d6a8ce android.hardware.neuralnetworks@1.3::IPreparedModelCallback
-306fda32ac969fd51d75d066352cadcb769944ec4823be4cdd3f86fdb9e97511 android.hardware.neuralnetworks@1.3::types
+dd39887aa4fb60ce60ea9cc043edeadbbae6e922d09d3946311b0b410024ae14 android.hardware.neuralnetworks@1.3::types
 3e01d4446cd69fd1c48f8572efd97487bc179564b32bd795800b97bbe10be37b android.hardware.wifi@1.4::IWifi
 a64467bae843569f0d465c5be7f0c7a5b987985b55a3ef4794dd5afc68538650 android.hardware.wifi.supplicant@1.3::ISupplicant
 44445b8a03d7b9e68b2fbd954672c18a8fce9e32851b0692f4f4ab3407f86ecb android.hardware.wifi.supplicant@1.3::ISupplicantStaIface
diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index 993a105..f0fd769 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -2314,7 +2314,38 @@
     AXIS_ALIGNED_BBOX_TRANSFORM = 41,
 
     /**
-     * Performs a forward LSTM on the input followed by a backward LSTM.
+     * A recurrent neural network layer that applies an LSTM cell to a
+     * sequence of inputs in forward and backward directions.
+     *
+     * The op supports cross-linking via an auxiliary input. Regular cell feeds
+     * one input into the two RNN cells in the following way:
+     *
+     *       INPUT  (INPUT_REVERSED)
+     *         |         |
+     *    ---------------------
+     *    | FW_LSTM   BW_LSTM |
+     *    ---------------------
+     *         |         |
+     *      FW_OUT     BW_OUT
+     *
+     * An op with cross-linking takes two inputs and feeds them into the RNN
+     * cells in the following way:
+     *
+     *       AUX_INPUT   (AUX_INPUT_REVERSED)
+     *           |             |
+     *     INPUT | (INPUT_R'D.)|
+     *       |   |       |     |
+     *    -----------------------
+     *    |  \  /        \    / |
+     *    | FW_LSTM     BW_LSTM |
+     *    -----------------------
+     *         |           |
+     *      FW_OUT      BW_OUT
+     *
+     * The cross-linking mode is enabled iff auxiliary input and auxiliary
+     * weights are present. While stacking this op on top of itself, this
+     * allows to connect both forward and backward outputs from previous cell
+     * to the next cell's input.
      *
      * Supported tensor {@link OperandType}:
      * * {@link OperandType::TENSOR_FLOAT16}
@@ -2324,7 +2355,6 @@
      *
      * All input and output tensors must be of the same type.
      *
-     *
      * Inputs:
      * * 0: The input.
      *      A 3-D tensor of shape:
@@ -2533,8 +2563,8 @@
      * * “activation” is the function passed as the “fused_activation_function”
      *   argument (if not “NONE”).
      *
-     * The op also supports an auxiliary input. Regular cell feeds one input
-     * into the two RNN cells in the following way:
+     * The op supports cross-linking via an auxiliary input. Regular cell feeds
+     * one input into the two RNN cells in the following way:
      *
      *       INPUT  (INPUT_REVERSED)
      *         |         |
@@ -2544,8 +2574,8 @@
      *         |         |
      *      FW_OUT     BW_OUT
      *
-     * An op with an auxiliary input takes two inputs and feeds them into the
-     * RNN cells in the following way:
+     * An op with cross-linking takes two inputs and feeds them into the RNN
+     * cells in the following way:
      *
      *       AUX_INPUT   (AUX_INPUT_REVERSED)
      *           |             |
@@ -2558,9 +2588,10 @@
      *         |           |
      *      FW_OUT      BW_OUT
      *
-     * While stacking this op on top of itself, this allows to connect both
-     * forward and backward outputs from previous cell to the next cell's
-     * inputs.
+     * The cross-linking mode is enabled iff auxiliary input and auxiliary
+     * weights are present. While stacking this op on top of itself, this
+     * allows to connect both forward and backward outputs from previous cell
+     * to the next cell's input.
      *
      * Supported tensor {@link OperandType}:
      * * {@link OperandType::TENSOR_FLOAT16}
diff --git a/neuralnetworks/1.3/types.hal b/neuralnetworks/1.3/types.hal
index a808a2e..08d8e6b 100644
--- a/neuralnetworks/1.3/types.hal
+++ b/neuralnetworks/1.3/types.hal
@@ -2364,7 +2364,54 @@
     AXIS_ALIGNED_BBOX_TRANSFORM = @1.2::OperationType:AXIS_ALIGNED_BBOX_TRANSFORM,
 
     /**
-     * Performs a forward LSTM on the input followed by a backward LSTM.
+     * A recurrent neural network layer that applies an LSTM cell to a
+     * sequence of inputs in forward and backward directions.
+     *
+     * The op supports cross-linking via an auxiliary input. Regular cell feeds
+     * one input into the two RNN cells in the following way:
+     *
+     *       INPUT  (INPUT_REVERSED)
+     *         |         |
+     *    ---------------------
+     *    | FW_LSTM   BW_LSTM |
+     *    ---------------------
+     *         |         |
+     *      FW_OUT     BW_OUT
+     *
+     * An op with cross-linking takes two inputs and feeds them into the RNN
+     * cells in the following way:
+     *
+     *       AUX_INPUT   (AUX_INPUT_REVERSED)
+     *           |             |
+     *     INPUT | (INPUT_R'D.)|
+     *       |   |       |     |
+     *    -----------------------
+     *    |  \  /        \    / |
+     *    | FW_LSTM     BW_LSTM |
+     *    -----------------------
+     *         |           |
+     *      FW_OUT      BW_OUT
+     *
+     * The cross-linking mode is enabled iff auxiliary input and auxiliary
+     * weights are present. While stacking this op on top of itself, this
+     * allows to connect both forward and backward outputs from previous cell
+     * to the next cell's input.
+     *
+     * Since HAL version 1.3 parallel linking mode is supported. The mode is
+     * enabled if auxiliary input is present but auxiliary weights are omitted.
+     * In this case, the cell feeds inputs into the RNN in the following way:
+     *
+     *       INPUT (AUX_INPUT_REVERSED)
+     *         |         |
+     *    ---------------------
+     *    | FW_LSTM   BW_LSTM |
+     *    ---------------------
+     *         |         |
+     *      FW_OUT     BW_OUT
+     *
+     * While stacking this op on top of itself, this allows to connect both
+     * forward and backward outputs from previous cell to the next cell's
+     * corresponding inputs.
      *
      * Supported tensor {@link OperandType}:
      * * {@link OperandType::TENSOR_FLOAT16}
@@ -2374,7 +2421,6 @@
      *
      * All input and output tensors must be of the same type.
      *
-     *
      * Inputs:
      * * 0: The input.
      *      A 3-D tensor of shape:
@@ -2466,25 +2512,34 @@
      * * 38: The backward input cell state.
      *       A 2-D tensor of shape [batch_size, bw_num_units].
      * * 39: The auxiliary input. Optional.
-     *       A 3-D tensor of shape [max_time, batch_size, input_size], where “batch_size”
-     *       corresponds to the batching dimension, and “input_size” is the size
-     *       of the input.
-     * * 40: The forward auxiliary input-to-input weights. Optional.
-     *       A 2-D tensor of shape [fw_num_units, input_size].
-     * * 41: The forward auxiliary input-to-forget weights. Optional.
-     *       A 2-D tensor of shape [fw_num_units, input_size].
-     * * 42: The forward auxiliary input-to-cell weights. Optional.
-     *       A 2-D tensor of shape [fw_num_units, input_size].
-     * * 43: The forward auxiliary input-to-output weights. Optional.
-     *       A 2-D tensor of shape [fw_num_units, input_size].
-     * * 44: The backward auxiliary input-to-input weights. Optional.
-     *       A 2-D tensor of shape [bw_num_units, input_size].
-     * * 45: The backward auxiliary input-to-forget weights. Optional.
-     *       A 2-D tensor of shape [bw_num_units, input_size].
-     * * 46: The backward auxiliary input-to-cell weights. Optional.
-     *       A 2-D tensor of shape [bw_num_units, input_size].
-     * * 47: The backward auxiliary input-to-output weights. Optional.
-     *       A 2-D tensor of shape [bw_num_units, input_size].
+     *       A 3-D tensor of shape [max_time, batch_size, aux_input_size],
+     *       where “batch_size” corresponds to the batching dimension, and
+     *       “aux_input_size” is the size of the auxiliary input. Optional. See
+     *       the docs above for the usage modes explanation.
+     * * 40: The forward auxiliary input-to-input weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [fw_num_units, aux_input_size].
+     * * 41: The forward auxiliary input-to-forget weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [fw_num_units, aux_input_size].
+     * * 42: The forward auxiliary input-to-cell weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [fw_num_units, aux_input_size].
+     * * 43: The forward auxiliary input-to-output weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [fw_num_units, aux_input_size].
+     * * 44: The backward auxiliary input-to-input weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [bw_num_units, aux_input_size].
+     * * 45: The backward auxiliary input-to-forget weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [bw_num_units, aux_input_size].
+     * * 46: The backward auxiliary input-to-cell weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [bw_num_units, aux_input_size].
+     * * 47: The backward auxiliary input-to-output weights.
+     *       Optional. See the docs above for the usage modes explanation.
+     *       A 2-D tensor of shape [bw_num_units, aux_input_size].
      * * 48: The activation function.
      *       A value indicating the activation function:
      *       <ul>
@@ -2607,8 +2662,8 @@
      * * “activation” is the function passed as the “fused_activation_function”
      *   argument (if not “NONE”).
      *
-     * The op also supports an auxiliary input. Regular cell feeds one input
-     * into the two RNN cells in the following way:
+     * The op supports cross-linking via an auxiliary input. Regular cell feeds
+     * one input into the two RNN cells in the following way:
      *
      *       INPUT  (INPUT_REVERSED)
      *         |         |
@@ -2618,8 +2673,8 @@
      *         |         |
      *      FW_OUT     BW_OUT
      *
-     * An op with an auxiliary input takes two inputs and feeds them into the
-     * RNN cells in the following way:
+     * An op with cross-linking takes two inputs and feeds them into the RNN
+     * cells in the following way:
      *
      *       AUX_INPUT   (AUX_INPUT_REVERSED)
      *           |             |
@@ -2632,9 +2687,26 @@
      *         |           |
      *      FW_OUT      BW_OUT
      *
+     * The cross-linking mode is enabled iff auxiliary input and auxiliary
+     * weights are present. While stacking this op on top of itself, this
+     * allows to connect both forward and backward outputs from previous cell
+     * to the next cell's input.
+     *
+     * Since HAL version 1.3 parallel linking mode is supported. The mode is
+     * enabled if auxiliary input is present but auxiliary weights are omitted.
+     * In this case, the cell feeds inputs into the RNN in the following way:
+     *
+     *       INPUT (AUX_INPUT_REVERSED)
+     *         |         |
+     *    ---------------------
+     *    | FW_RNN     BW_RNN |
+     *    ---------------------
+     *         |         |
+     *      FW_OUT     BW_OUT
+     *
      * While stacking this op on top of itself, this allows to connect both
      * forward and backward outputs from previous cell to the next cell's
-     * inputs.
+     * corresponding inputs.
      *
      * Supported tensor {@link OperandType}:
      * * {@link OperandType::TENSOR_FLOAT16}
@@ -2667,11 +2739,17 @@
      *      A 2-D tensor of shape [batchSize, bwNumUnits]. Specifies a hidden
      *      state input for the first time step of the computation.
      * * 9: auxInput.
-     *      A 3-D tensor. The shape is the same as of the input 0.
+     *      A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
+     *      it is set to true, then the input has a shape [maxTime, batchSize,
+     *      auxInputSize], otherwise the input has a shape [batchSize, maxTime,
+     *      auxInputSize]. Can be omitted. See the docs above for the usage
+     *      modes explanation.
      * * 10:fwAuxWeights.
-     *      A 2-D tensor of shape [fwNumUnits, inputSize].
+     *      A 2-D tensor of shape [fwNumUnits, auxInputSize]. Can be omitted.
+     *      See the docs above for the usage modes explanation.
      * * 11:bwAuxWeights.
-     *      A 2-D tensor of shape [bwNumUnits, inputSize].
+     *      A 2-D tensor of shape [bwNumUnits, auxInputSize]. Can be omitted.
+     *      See the docs above for the usage modes explanation.
      * * 12:fusedActivationFunction.
      *      A {@link FusedActivationFunc} value indicating the activation function. If
      *      “NONE” is specified then it results in a linear activation.