diff --git a/binaries.json b/binaries.json
index e5e7a17a7144..d74dcf6f8531 100644
--- a/binaries.json
+++ b/binaries.json
@@ -5,11 +5,9 @@
             {
                 "utils": [
                     "C",
-                    "CC",
                     "CD",
                     "CI",
                     "CL",
-                    "CM",
                     "CV",
                     "CX",
                     "D",
@@ -43,7 +41,6 @@
                     "III",
                     "IIL",
                     "IIM",
-                    "IIV",
                     "IIX",
                     "IL",
                     "ILC",
@@ -62,7 +59,6 @@
                     "IMV",
                     "IMX",
                     "IV",
-                    "IVC",
                     "IVD",
                     "IVI",
                     "IVL",
@@ -103,7 +99,13 @@
                     "VCV",
                     "VCX",
                     "VD",
+                    "VDC",
+                    "VDD",
                     "VDI",
+                    "VDL",
+                    "VDM",
+                    "VDV",
+                    "VDX",
                     "VI",
                     "VIC",
                     "VID",
@@ -149,4 +151,4 @@
             }
         ]
     }
-}
+}
\ No newline at end of file
diff --git a/ivy/compiler/compiler.py b/ivy/compiler/compiler.py
index 4cec6f1c0d97..c59dc9a8340d 100644
--- a/ivy/compiler/compiler.py
+++ b/ivy/compiler/compiler.py
@@ -2,15 +2,15 @@
 
 
 def clear_graph_cache():
-    """Clears the graph cache which gets populated if `graph_caching` is set to
-    `True` in `ivy.trace_graph`, `ivy.transpile` or `ivy.unify`. Use this to
+    """Clears the graph cache which gets populated if `graph_caching` is set
+    to `True` in `ivy.trace_graph`, `ivy.transpile` or `ivy.unify`. Use this to
     reset or clear the graph cache if needed.
 
     Examples
     --------
     >>> import ivy
-    >>> ivy.clear_graph_cache()
-    """
+    >>> ivy.clear_graph_cache()"""
+
     from ._compiler import clear_graph_cache as _clear_graph_cache
 
     return _clear_graph_cache()
@@ -55,8 +55,8 @@ def graph_transpile(
 
     Returns
     -------
-    Either a transpiled Graph or a non-initialized LazyGraph.
-    """
+    Either a transpiled Graph or a non-initialized LazyGraph."""
+
     from ._compiler import graph_transpile as _graph_transpile
 
     return _graph_transpile(
@@ -96,7 +96,6 @@ def source_to_source(
     e.g. (source="torch_frontend", target="ivy") or (source="torch_frontend", target="tensorflow") etc.
 
     Args:
-    ----
         object: The object (class/function) to be translated.
         source (str, optional): The source framework. Defaults to 'torch'.
         target (str, optional): The target framework. Defaults to 'tensorflow'.
@@ -107,9 +106,8 @@ def source_to_source(
                                          the old implementation. Defaults to 'True'.
 
     Returns:
-    -------
-    The translated object.
-    """
+        The translated object."""
+
     from ._compiler import source_to_source as _source_to_source
 
     return _source_to_source(
@@ -140,8 +138,7 @@ def trace_graph(
     params_v=None,
     v=None
 ):
-    """Takes `fn` and traces it into a more efficient composition of backend
-    operations.
+    """Takes `fn` and traces it into a more efficient composition of backend operations.
 
     Parameters
     ----------
@@ -211,8 +208,8 @@ def trace_graph(
     >>> start = time.time()
     >>> graph(x)
     >>> print(time.time() - start)
-    0.0001785755157470703
-    """
+    0.0001785755157470703"""
+
     from ._compiler import trace_graph as _trace_graph
 
     return _trace_graph(
@@ -252,7 +249,6 @@ def transpile(
     e.g. (source="torch_frontend", target="ivy") or (source="torch_frontend", target="tensorflow") etc.
 
     Args:
-    ----
         object: The object (class/function) to be translated.
         source (str, optional): The source framework. Defaults to 'torch'.
         target (str, optional): The target framework. Defaults to 'tensorflow'.
@@ -263,9 +259,8 @@ def transpile(
                                          the old implementation. Defaults to 'True'.
 
     Returns:
-    -------
-    The translated object.
-    """
+        The translated object."""
+
     from ._compiler import transpile as _transpile
 
     return _transpile(
diff --git a/ivy/functional/backends/tensorflow/general.py b/ivy/functional/backends/tensorflow/general.py
index d44f3490f984..eb342e66e6df 100644
--- a/ivy/functional/backends/tensorflow/general.py
+++ b/ivy/functional/backends/tensorflow/general.py
@@ -61,7 +61,51 @@ def get_item(
 ) -> Union[tf.Tensor, tf.Variable]:
     if ivy.is_array(query) and ivy.is_bool_dtype(query) and not len(query.shape):
         return tf.expand_dims(x, 0)
-    return x[query]
+    if isinstance(query, (tf.Tensor, tf.Variable)):
+        if query.dtype == tf.bool:
+            return tf.boolean_mask(x, query, axis=0)
+        else:
+            query = tf.cast(query, tf.int64)
+            return tf.gather(x, query, axis=0)
+    else:
+        if any([isinstance(q, slice) for q in query]):
+            # convert any lists/tuples within the query to slices
+            query = tuple([slice(*q) if isinstance(q, (list, tuple)) else q for q in query])
+        # for slices and other basic indexing, use __getitem__
+        return x[query]
+
+
+def set_item(
+    x: Union[tf.Tensor, tf.Variable],
+    query: Union[tf.Tensor, tf.Variable, Tuple],
+    val: Union[tf.Tensor, tf.Variable],
+    /,
+    *,
+    copy: Optional[bool] = False,
+) -> Union[tf.Tensor, tf.Variable]:
+    # TODO: we should re-write this at some point so it's compatible with tf.function (don't use numpy as an intermediary)
+    # when doing this, be sure to check the performance of the function on large tensors, compared to this implementation
+
+    if tf.is_tensor(x):
+        x = x.numpy()
+    if tf.is_tensor(val):
+        val = val.numpy()
+
+    if isinstance(query, (tf.Tensor, tf.Variable)):
+        query = query.numpy()
+    elif isinstance(query, tuple):
+        query = tuple(
+            q.numpy() if isinstance(q, (tf.Tensor, tf.Variable)) else q
+            for q in query
+        )
+
+    x[query] = val
+
+    if isinstance(x, tf.Variable) and not copy:
+        x.assign(x)
+        return x
+    else:
+        return tf.Variable(x) if isinstance(x, tf.Variable) else tf.convert_to_tensor(x)
 
 
 def to_numpy(x: Union[tf.Tensor, tf.Variable], /, *, copy: bool = True) -> np.ndarray:
diff --git a/ivy/functional/ivy/general.py b/ivy/functional/ivy/general.py
index fceb0fc4eca7..f4f966cd4a8f 100644
--- a/ivy/functional/ivy/general.py
+++ b/ivy/functional/ivy/general.py
@@ -2879,25 +2879,7 @@ def set_item(
     ivy.array([[ 0, -1, 20],
            [10, 10, 10]])
     """
-    if copy:
-        x = ivy.copy_array(x)
-    if not ivy.is_array(val):
-        val = ivy.array(val)
-    if 0 in x.shape or 0 in val.shape:
-        return x
-    if ivy.is_array(query) and ivy.is_bool_dtype(query):
-        if not len(query.shape):
-            query = ivy.tile(query, (x.shape[0],))
-        indices = ivy.nonzero(query, as_tuple=False)
-    else:
-        indices, target_shape, _ = _parse_query(
-            query, ivy.shape(x, as_array=True), scatter=True
-        )
-        if indices is None:
-            return x
-    val = val.astype(x.dtype)
-    ret = ivy.scatter_nd(indices, val, reduction="replace", out=x)
-    return ret
+    return current_backend(x).set_item(x, query, val, copy=copy)
 
 
 set_item.mixed_backend_wrappers = {
diff --git a/ivy/utils/decorator_utils.py b/ivy/utils/decorator_utils.py
index 177ae7669a8e..222be4139c5e 100644
--- a/ivy/utils/decorator_utils.py
+++ b/ivy/utils/decorator_utils.py
@@ -183,8 +183,6 @@ def handle_get_item(fn):
     def wrapper(inp, query, **kwargs):
         try:
             res = inp.__getitem__(query)
-        except IndexError:
-            raise
         except Exception:
             res = fn(inp, query, **kwargs)
         return res