diff --git a/torch_geometric/utils/augmentation.py b/torch_geometric/utils/augmentation.py
index 82b07a67..357ac1ed 100644
--- a/torch_geometric/utils/augmentation.py
+++ b/torch_geometric/utils/augmentation.py
@@ -204,7 +204,7 @@ def add_random_edge(edge_index, p: float, force_undirected: bool = False,
         tensor([[0, 1, 2, 3, 4, 5, 3, 4, 1],
                 [2, 3, 1, 4, 2, 1, 1, 3, 2]])
         >>> added_edges
-        tensor([[3, 4, 1],
+        tensor([[3, 4, 1]
                 [1, 3, 2]])
     """
     if p < 0. or p > 1.:
@@ -232,6 +232,40 @@ def add_random_edge(edge_index, p: float, force_undirected: bool = False,
         mask = row < col
         row, col = row[mask], col[mask]
         row, col = torch.cat([row, col]), torch.cat([col, row])
-    edge_index_to_add = torch.stack([row, col], dim=0).to(device)
+    
+    # Filter out edges that already exist in the original graph
+    # Convert to lists for efficient lookup
+    src_list = edge_index[0].tolist()
+    dst_list = edge_index[1].tolist()
+    
+    # Create mask for new edges that don't already exist
+    new_edge_mask = []
+    for i in range(len(row)):
+        s, d = row[i].item(), col[i].item()
+        # Check if edge (s,d) already exists
+        exists = False
+        for j in range(len(src_list)):
+            if src_list[j] == s and dst_list[j] == d:
+                exists = True
+                break
+        new_edge_mask.append(not exists)
+    
+    # Apply mask to keep only non-existing edges
+    if len(row) > 0:
+        mask_tensor = torch.tensor(new_edge_mask, dtype=torch.bool, device=device)
+        row = row[mask_tensor]
+        col = col[mask_tensor]
+        edge_index_to_add = torch.stack([row, col], dim=0)
+        
+        if force_undirected:
+            # For undirected case, we need to rebuild the symmetric pairs
+            # since filtering might have removed one direction but not the other
+            edge_index_to_add = torch.cat([
+                edge_index_to_add, 
+                torch.stack([col, row], dim=0)
+            ], dim=1)
+    else:
+        edge_index_to_add = torch.empty((2, 0), dtype=torch.long, device=device)
+    
     edge_index = torch.cat([edge_index, edge_index_to_add], dim=1)
-    return edge_index, edge_index_to_add
+    return edge_index, edge_index_to_add
\ No newline at end of file