diff --git a/backends/arm/_passes/arm_pass_manager.py b/backends/arm/_passes/arm_pass_manager.py
index 2cf8727ac8a..c234ce3db9b 100644
--- a/backends/arm/_passes/arm_pass_manager.py
+++ b/backends/arm/_passes/arm_pass_manager.py
@@ -320,6 +320,7 @@ def _tosa_pipeline(
             [
                 ReplaceScalarWithTensorByProfilePass(),
                 RewriteLeLtToGeGtPass(),
+                DecomposeLeakyReLUPass(),  # Emits full_like so before ConvertFullLikeToFullPass
                 ConvertFullLikeToFullPass(),
                 MatchArgDtypePass(),
                 UnsqueezeScalarPlaceholdersPass(exported_program),
@@ -340,7 +341,6 @@ def _tosa_pipeline(
                 FuseBatchNorm2dPass(exported_program),
                 ConvertMmToBmmPass(),
                 DecomposeGluPass(),
-                DecomposeLeakyReLUPass(),
                 DecomposeDivPass(),
                 # _safe_softmax results in a ReduceMax
                 # which is not currently supported by TOSA in U55
diff --git a/backends/arm/_passes/decompose_leaky_relu_pass.py b/backends/arm/_passes/decompose_leaky_relu_pass.py
index 5fbf8b9e035..d9b5bbe96df 100644
--- a/backends/arm/_passes/decompose_leaky_relu_pass.py
+++ b/backends/arm/_passes/decompose_leaky_relu_pass.py
@@ -9,6 +9,9 @@
 
 import torch
 from executorch.backends.arm._passes import ArmPass
+from executorch.backends.arm._passes.convert_full_like_to_full_pass import (
+    ConvertFullLikeToFullPass,
+)
 from executorch.exir.dialects._ops import ops as exir_ops
 from executorch.exir.pass_base import ExportPass
 
@@ -20,14 +23,14 @@ def _get_leaky_relu_ops(op) -> tuple:
     if op in edge_ops:
         return (
             exir_ops.edge.aten.clamp.default,
-            exir_ops.edge.aten.full.default,
+            exir_ops.edge.aten.full_like.default,
             exir_ops.edge.aten.mul.Tensor,
             exir_ops.edge.aten.add.Tensor,
         )
     elif op in torch_ops:
         return (
             torch.ops.aten.clamp.default,
-            torch.ops.aten.full.default,
+            torch.ops.aten.full_like.default,
             torch.ops.aten.mul.Tensor,
             torch.ops.aten.add.Tensor,
         )
@@ -42,13 +45,13 @@ class DecomposeLeakyReLUPass(ArmPass):
     Example:
         %op1 = clamp(x,0,None) (equivalent to max(0,x))
         %op2 = clamp(x,None,0) (equivalent to min(0,x))
-        %op3 = full(x.shape,slope)
+        %op3 = full_like(x,slope)
         %op4 = mul(%op3,%op2)
         %op5 = add(%op1,%op4)
 
     """
 
-    _passes_required_after: Set[Type[ExportPass]] = set()
+    _passes_required_after: Set[Type[ExportPass]] = {ConvertFullLikeToFullPass}
 
     def call_operator(self, op, args, kwargs, meta):
         if op not in (edge_ops + torch_ops) or not self.allowed_to_transform(meta):
@@ -56,9 +59,7 @@ def call_operator(self, op, args, kwargs, meta):
 
         x = args[0]
         slope = args[1] if len(args) > 1 else 0.01
-        dtype = x.node.meta["val"].dtype
-        device = x.node.meta["val"].device
-        clamp, full, mul, add = _get_leaky_relu_ops(op)
+        clamp, full_like, mul, add = _get_leaky_relu_ops(op)
         op1 = super().call_operator(
             op=clamp, args=(x, 0, None), kwargs=kwargs, meta=meta
         )
@@ -66,9 +67,9 @@ def call_operator(self, op, args, kwargs, meta):
             op=clamp, args=(x, None, 0), kwargs=kwargs, meta=meta
         )
         op3 = super().call_operator(
-            op=full,
-            args=(x.node.meta["val"].shape, slope),
-            kwargs={"dtype": dtype, "device": device},
+            op=full_like,
+            args=(x, slope),
+            kwargs={},
             meta=meta,
         )
         op4 = super().call_operator(op=mul, args=(op3, op2), kwargs=kwargs, meta=meta)