diff --git a/current.txt b/current.txt
index 1d1b80a..428c15e 100644
--- a/current.txt
+++ b/current.txt
@@ -401,8 +401,8 @@
 65a021fa89085b62fc96b2b6d3bef2f9103cf4d63379c68bc154fd9eef672852 android.hardware.health@1.0::types
 b7ecf29927055ec422ec44bf776223f07d79ad9f92ccf9becf167e62c2607e7a android.hardware.keymaster@4.0::IKeymasterDevice
 574e8f1499436fb4075894dcae0b36682427956ecb114f17f1fe22d116a83c6b android.hardware.neuralnetworks@1.0::IPreparedModel
-417ab60fe1ef786778047e4486f3d868ebce570d91addd8fe4251515213072de android.hardware.neuralnetworks@1.0::types
-ec8aa14fe9b03f2b3fb9845346a4005b6d098ebe2277b2564f73a548a0fd14a7 android.hardware.neuralnetworks@1.1::types
+567de4ebb3a224721eabae40c4484fad2cd1608eb0e66ec9214eb88e9b15d3c9 android.hardware.neuralnetworks@1.0::types
+d51937a3567a50f239589e40300264c4b57f2c3582c6fc6df082f45eb74d90e3 android.hardware.neuralnetworks@1.1::types
 1d4a5776614c08b5d794a5ec5ab04697260cbd4b3441d5935cd53ee71d19da02 android.hardware.radio@1.0::IRadioResponse
 ed9da80ec0c96991fd03f0a46107815d0e50f764656e49dba4980fa5c31d5bc3 android.hardware.radio@1.0::types
 1d19720d4fd38b1095f0f555a4bd92b3b12c9b1d0f560b0e9a474cd6dcc20db6 android.hardware.radio@1.2::IRadio
@@ -515,7 +515,7 @@
 92714960d1a53fc2ec557302b41c7cc93d2636d8364a44bd0f85be0c92927ff8 android.hardware.neuralnetworks@1.2::IExecutionCallback
 36e1064c869965dee533c537cefbe87e54db8bd8cd45be7e0e93e00e8a43863a android.hardware.neuralnetworks@1.2::IPreparedModel
 e1c734d1545e1a4ae749ff1dd9704a8e594c59aea7c8363159dc258e93e0df3b android.hardware.neuralnetworks@1.2::IPreparedModelCallback
-b75126d572c1788682a679ab53c2dbdf3fcd75f754b1370dbf09aaad0e19d397 android.hardware.neuralnetworks@1.2::types
+b47700929d91ad9c037fd26077d4008d4a04753f71f4f332aeedbd1de7bb91e1 android.hardware.neuralnetworks@1.2::types
 cf7a4ba516a638f9b82a249c91fb603042c2d9ca43fd5aad9cf6c0401ed2a5d7 android.hardware.nfc@1.2::INfc
 abf98c2ae08bf765db54edc8068e36d52eb558cff6706b6fd7c18c65a1f3fc18 android.hardware.nfc@1.2::types
 4cb252dc6372a874aef666b92a6e9529915aa187521a700f0789065c3c702ead android.hardware.power.stats@1.0::IPowerStats
diff --git a/neuralnetworks/1.0/types.hal b/neuralnetworks/1.0/types.hal
index 89af35a..a358946 100644
--- a/neuralnetworks/1.0/types.hal
+++ b/neuralnetworks/1.0/types.hal
@@ -1197,6 +1197,11 @@
      *      shape of the output tensor. The number of elements implied by shape
      *      must be the same as the number of elements in the input tensor.
      *
+     *      If one component of shape is the special value -1, the size of that
+     *      dimension is computed so that the total size remains constant. In
+     *      particular, a shape of [-1] flattens into 1-D. At most one component
+     *      of shape can be -1.
+     *
      * Outputs:
      * * 0: The output tensor, of shape specified by the input shape.
      *
diff --git a/neuralnetworks/1.1/types.hal b/neuralnetworks/1.1/types.hal
index 99f873a..335b803 100644
--- a/neuralnetworks/1.1/types.hal
+++ b/neuralnetworks/1.1/types.hal
@@ -104,9 +104,6 @@
      * in axis. If keep_dims is true, the reduced dimensions are retained with
      * length 1.
      *
-     * If dimensions to reduce have no entries, all dimensions are reduced, and
-     * a tensor with a single element is returned.
-     *
      * Supported tensor {@link OperandType}:
      * * {@link OperandType::TENSOR_FLOAT32}
      * * {@link OperandType::TENSOR_QUANT8_ASYMM}
@@ -116,8 +113,14 @@
      * Inputs:
      * * 0: A tensor, specifying the input.
      * * 1: A 1-D Tensor of {@link OperandType::TENSOR_INT32}. The dimensions
-     *      to reduce. If None (the default), reduces all dimensions. Must be in
-     *      the range [-rank(input_tensor), rank(input_tensor)).
+     *      to reduce. Must be in the range
+     *      [-rank(input_tensor), rank(input_tensor)).
+     *
+     *      NOTE: When the operation was introduced, the documentation
+     *      incorrectly stated that if dimensions were empty, the operation
+     *      would reduce across all dimensions. This behavior was never
+     *      implemented.
+     *
      * * 2: An {@link OperandType::INT32} scalar, keep_dims. If positive,
      *      retains reduced dimensions with length 1.
      *
diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index 839114f..499c817 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -1548,6 +1548,11 @@
      *      shape of the output tensor. The number of elements implied by shape
      *      must be the same as the number of elements in the input tensor.
      *
+     *      If one component of shape is the special value -1, the size of that
+     *      dimension is computed so that the total size remains constant. In
+     *      particular, a shape of [-1] flattens into 1-D. At most one component
+     *      of shape can be -1.
+     *
      * Outputs:
      * * 0: The output tensor, of shape specified by the input shape.
      *
@@ -1949,9 +1954,6 @@
      * in axis. If keep_dims is true, the reduced dimensions are retained with
      * length 1.
      *
-     * If dimensions to reduce have no entries, all dimensions are reduced, and
-     * a tensor with a single element is returned.
-     *
      * Supported tensor {@link OperandType}:
      * * {@link OperandType::TENSOR_FLOAT16} (since API level 29)
      * * {@link OperandType::TENSOR_FLOAT32}
@@ -1962,8 +1964,14 @@
      * Inputs:
      * * 0: A tensor, specifying the input.
      * * 1: A 1-D Tensor of {@link OperandType::TENSOR_INT32}. The dimensions
-     *      to reduce. If None (the default), reduces all dimensions. Must be in
-     *      the range [-rank(input_tensor), rank(input_tensor)).
+     *      to reduce. Must be in the range
+     *      [-rank(input_tensor), rank(input_tensor)).
+     *
+     *      NOTE: When the operation was introduced, the documentation
+     *      incorrectly stated that if dimensions were empty, the operation
+     *      would reduce across all dimensions. This behavior was never
+     *      implemented.
+     *
      * * 2: An {@link OperandType::INT32} scalar, keep_dims. If positive,
      *      retains reduced dimensions with length 1.
      *