### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

When running a DAG that is structured like:
```
@dag{dag_id="my_dag", default_args={"retries":0"}}
def dag():
    op = MyOperator.partial(task_id="my_task", retries=3).expand(...)
```

The following test fails:
```
    def test_retries(self) -> None:
        dag_bag = DagBag(dag_folder=DAG_FOLDER, include_examples=False)
        dag = dag_bag.dags["my_dag"]
        for task in dag.tasks:
            if "my_task" in task.task_id:
                self.assertEqual(3, task.retries) # fails - this is 0
```

When printing out `task.partial_kwargs`, and looking at how the default args and partial args are merged, it seems like the default args are always taking precedence, even though in the `partial` global function, the `retries` do get set later on with the task-level parameter value. This doesn't seem to be respected though.

### What you think should happen instead

_No response_

### How to reproduce

If you run my above unit test for a test DAG, on version 2.4.3, it should show up as a test failure.

### Operating System

OS Ventura

### Versions of Apache Airflow Providers

_No response_

### Deployment

Google Cloud Composer

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""Required by DAGNode."""
        return DagAttributeTypes.OP, self.task_id
    @property
    def inherits_from_empty_operator(self):
        """Used to determine if an Operator is inherited from EmptyOperator"""
        
        
        
        return getattr(self, "_is_empty", False)
    def defer(
        self,
        *,
        trigger: BaseTrigger,
        method_name: str,
        kwargs: dict[str, Any] | None = None,
        timeout: timedelta | None = None,
    ):
        """
        Marks this Operator as being "deferred" - that is, suspending its
        execution until the provided trigger fires an event.
        This is achieved by raising a special exception (TaskDeferred)
        which is caught in the main _execute_task wrapper.
        """
        raise TaskDeferred(trigger=trigger, method_name=method_name, kwargs=kwargs, timeout=timeout)
    def unmap(self, resolve: None | dict[str, Any] | tuple[Context, Session]) -> BaseOperator: