diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml
index 9746e51e84..21077afdd3 100644
--- a/.github/workflows/testing.yml
+++ b/.github/workflows/testing.yml
@@ -108,7 +108,7 @@ jobs:
           EMMET_USE_EMMET_MODELS: true
         run: python${{ matrix.python-version }} -m pytest -n auto --cov=emmet --cov-report=xml ${{ matrix.package }}/tests
 
-      - uses: codecov/codecov-action@v5.5.1
+      - uses: codecov/codecov-action@v5.5.2
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
           file: ./coverage.xml
diff --git a/emmet-core/emmet/core/trajectory.py b/emmet-core/emmet/core/trajectory.py
index 636bbb6b58..f829e0b9be 100644
--- a/emmet-core/emmet/core/trajectory.py
+++ b/emmet-core/emmet/core/trajectory.py
@@ -740,10 +740,11 @@ def from_vasprun(
         ):
             kwargs["time_step"] = vasprun.parameters.get("POTIM")
 
+        istep_attr = "md_data" if vasprun.incar.get("ML_LMLFF") else "ionic_steps"
         return cls._from_dict(
             {
                 remap.get(k, k): [
-                    ionic_step.get(k) for ionic_step in vasprun.ionic_steps
+                    ionic_step.get(k) for ionic_step in getattr(vasprun, istep_attr, [])
                 ]
                 for k in ionic_step_data
             },
diff --git a/emmet-core/emmet/core/types/pymatgen_types/xas_adapter.py b/emmet-core/emmet/core/types/pymatgen_types/xas_adapter.py
index 59a875894c..c1d6a66888 100644
--- a/emmet-core/emmet/core/types/pymatgen_types/xas_adapter.py
+++ b/emmet-core/emmet/core/types/pymatgen_types/xas_adapter.py
@@ -1,5 +1,6 @@
-from typing import Annotated, TypeVar
+from typing import Any, Annotated, TypeVar
 
+import numpy as np
 from pydantic import BeforeValidator, WrapSerializer
 from pymatgen.analysis.xas.spectrum import XAS
 from typing_extensions import TypedDict
@@ -45,8 +46,18 @@ def pop_xas_empty_structure_fields(xas: XASTypeVar, eps: float = 1e-12):
     return xas
 
 
+def _serialize_xas(xas: XAS) -> dict[str, Any]:
+    xas_dct = xas.as_dict()
+    for k in ("x", "y"):
+        if isinstance(xas_dct[k], np.ndarray):
+            xas_dct[k] = xas_dct[k].tolist()
+    return xas_dct
+
+
 XASType = Annotated[
     XASTypeVar,
     BeforeValidator(pop_xas_empty_structure_fields),
-    WrapSerializer(lambda x, nxt, info: x.as_dict(), return_type=TypedXASSpectrumDict),
+    WrapSerializer(
+        lambda x, nxt, info: _serialize_xas(x), return_type=TypedXASSpectrumDict
+    ),
 ]