diff --git a/openx_rlds.py b/openx_rlds.py
index cf873a8..060a714 100644
--- a/openx_rlds.py
+++ b/openx_rlds.py
@@ -190,7 +190,12 @@ def create_lerobot_dataset(
 
     builder = tfds.builder(dataset_name, data_dir=data_dir, version=version)
     features = generate_features_from_raw(builder, use_videos)
-    raw_dataset = builder.as_dataset(split="train").map(partial(transform_raw_dataset, dataset_name=dataset_name))
+    filter_fn = lambda e: e["success"] if dataset_name == "kuka" else True
+    raw_dataset = (
+        builder.as_dataset(split="train")
+        .filter(filter_fn)
+        .map(partial(transform_raw_dataset, dataset_name=dataset_name))
+    )
 
     if fps is None:
         if dataset_name in OXE_DATASET_CONFIGS:
diff --git a/oxe_utils/transforms.py b/oxe_utils/transforms.py
index c845fc6..31a09a6 100644
--- a/oxe_utils/transforms.py
+++ b/oxe_utils/transforms.py
@@ -192,19 +192,6 @@ def kuka_dataset_transform(trajectory: Dict[str, Any]) -> Dict[str, Any]:
         ),
         axis=-1,
     )
-    # decode compressed state
-    eef_value = tf.io.decode_compressed(
-        trajectory["observation"]["clip_function_input/base_pose_tool_reached"],
-        compression_type="ZLIB",
-    )
-    eef_value = tf.io.decode_raw(eef_value, tf.float32)
-    trajectory["observation"]["clip_function_input/base_pose_tool_reached"] = tf.reshape(eef_value, (-1, 7))
-    gripper_value = tf.io.decode_compressed(trajectory["observation"]["gripper_closed"], compression_type="ZLIB")
-    gripper_value = tf.io.decode_raw(gripper_value, tf.float32)
-    trajectory["observation"]["gripper_closed"] = tf.reshape(gripper_value, (-1, 1))
-    # trajectory["language_instruction"] = tf.fill(
-    #     tf.shape(trajectory["observation"]["natural_language_instruction"]), ""
-    # )  # delete uninformative language instruction
     trajectory["language_instruction"] = trajectory["observation"]["natural_language_instruction"]
     return trajectory