diff --git a/torchrl/objectives/value/advantages.py b/torchrl/objectives/value/advantages.py
index d8d7c128857..bd73683ef0a 100644
--- a/torchrl/objectives/value/advantages.py
+++ b/torchrl/objectives/value/advantages.py
@@ -46,6 +46,8 @@ class TDEstimate(nn.Module):
             Defaults to "advantage".
         value_target_key (str or tuple of str, optional): the key of the advantage entry.
             Defaults to "value_target".
+        value_key (str or tuple of str, optional): the value key to read from the input tensordict.
+            Defaults to "state_value".
 
     """
 
@@ -57,6 +59,7 @@ def __init__(
         differentiable: bool = False,
         advantage_key: Union[str, Tuple] = "advantage",
         value_target_key: Union[str, Tuple] = "value_target",
+        value_key: Union[str, Tuple] = "state_value",
     ):
         super().__init__()
         try:
@@ -68,7 +71,11 @@ def __init__(
 
         self.average_rewards = average_rewards
         self.differentiable = differentiable
-        self.value_key = value_network.out_keys[0]
+        self.value_key = value_key
+        if value_key not in value_network.out_keys:
+            raise KeyError(
+                f"value key '{value_key}' not found in value network out_keys."
+            )
 
         self.advantage_key = advantage_key
         self.value_target_key = value_target_key
@@ -209,6 +216,8 @@ class TDLambdaEstimate(nn.Module):
             Defaults to "advantage".
         value_target_key (str or tuple of str, optional): the key of the advantage entry.
             Defaults to "value_target".
+        value_key (str or tuple of str, optional): the value key to read from the input tensordict.
+            Defaults to "state_value".
 
     """
 
@@ -222,6 +231,7 @@ def __init__(
         vectorized: bool = True,
         advantage_key: Union[str, Tuple] = "advantage",
         value_target_key: Union[str, Tuple] = "value_target",
+        value_key: Union[str, Tuple] = "state_value",
     ):
         super().__init__()
         try:
@@ -235,7 +245,11 @@ def __init__(
 
         self.average_rewards = average_rewards
         self.differentiable = differentiable
-        self.value_key = self.value_network.out_keys[0]
+        self.value_key = value_key
+        if value_key not in value_network.out_keys:
+            raise KeyError(
+                f"value key '{value_key}' not found in value network out_keys."
+            )
 
         self.advantage_key = advantage_key
         self.value_target_key = value_target_key
@@ -389,6 +403,8 @@ class GAE(nn.Module):
             Defaults to "advantage".
         value_target_key (str or tuple of str, optional): the key of the advantage entry.
             Defaults to "value_target".
+        value_key (str or tuple of str, optional): the value key to read from the input tensordict.
+            Defaults to "state_value".
 
     GAE will return an :obj:`"advantage"` entry containing the advange value. It will also
     return a :obj:`"value_target"` entry with the return value that is to be used
@@ -408,6 +424,7 @@ def __init__(
         differentiable: bool = False,
         advantage_key: Union[str, Tuple] = "advantage",
         value_target_key: Union[str, Tuple] = "value_target",
+        value_key: Union[str, Tuple] = "state_value",
     ):
         super().__init__()
         try:
@@ -417,7 +434,11 @@ def __init__(
         self.register_buffer("gamma", torch.tensor(gamma, device=device))
         self.register_buffer("lmbda", torch.tensor(lmbda, device=device))
         self.value_network = value_network
-        self.value_key = self.value_network.out_keys[0]
+        self.value_key = value_key
+        if value_key not in value_network.out_keys:
+            raise KeyError(
+                f"value key '{value_key}' not found in value network out_keys."
+            )
 
         self.average_gae = average_gae
         self.differentiable = differentiable