diff --git a/experimental/torch_xla2/test/test_ops.py b/experimental/torch_xla2/test/test_ops.py
index 9b0452734f10..9cdccbf525e7 100644
--- a/experimental/torch_xla2/test/test_ops.py
+++ b/experimental/torch_xla2/test/test_ops.py
@@ -119,7 +119,6 @@
     "linalg.vector_norm",
     "linspace",
     "log_normal",
-    "log_softmax",
     "logaddexp2",
     "logaddexp",
     "logcumsumexp",
@@ -252,8 +251,6 @@
     "scatter",
     "scatter_reduce",
     "searchsorted",
-    "softmax",
-    "sort",
     "special.airy_ai",
     "special.modified_bessel_i1",
     "special.modified_bessel_k0",
diff --git a/experimental/torch_xla2/torch_xla2/ops/jaten.py b/experimental/torch_xla2/torch_xla2/ops/jaten.py
index fce3bb45884e..18ddee041e99 100644
--- a/experimental/torch_xla2/torch_xla2/ops/jaten.py
+++ b/experimental/torch_xla2/torch_xla2/ops/jaten.py
@@ -220,6 +220,8 @@ def _aten_stack(tensors, dim=0):
 
 @op(torch.ops.aten._softmax)
 def _aten_softmax(x, dim, halftofloat):
+  if x.shape == ():
+      return jnp.astype(1.0, x.dtype)
   return jax.nn.softmax(x, dim)
 
 
@@ -1947,6 +1949,8 @@ def _aten_logical_not(self):
 # aten.log_softmax
 @op(torch.ops.aten._log_softmax)
 def _aten_log_softmax(self, axis=-1, half_to_float=False):
+  if self.shape == ():
+      return jnp.astype(0.0, self.dtype)
   return jax.nn.log_softmax(self, axis)
 
 
@@ -2024,6 +2028,8 @@ def _aten_slice_scatter(input, src, dim=0, start=None, end=None, step=1):
 # torch.sort(input, dim=-1, descending=False, stable=False, *, out=None)
 @op(torch.ops.aten.sort)
 def _aten_sort(a, dim=-1, descending=False, stable=False):
+  if a.shape == ():
+    return (a, jnp.astype(0, 'int64'))
   return (
     jnp.sort(a, axis=dim, stable=stable, descending=descending),
     jnp.argsort(a, axis=dim, stable=stable, descending=descending),