### Apache Airflow version

2.4.3

### What happened

A significant fraction of the DAG Runs of a DAG that has 2+ consecutive mapped tasks which are are being passed an empty list are marked as failed when all tasks are either succeeding or being skipped. This was supposedly fixed with issue #25200 but the problem still persists.
![image](https://user-images.githubusercontent.com/46539900/203193331-db94c793-36e8-4fbd-bc45-29865c44fbfc.png)

### What you think should happen instead

The DAG Run should be marked success.

### How to reproduce

The real world version of this DAG has several mapped tasks that all point to the same list, and that list is frequently empty. I have made a minimal reproducible example.

```
from datetime import datetime

from airflow import DAG
from airflow.decorators import task


with DAG(dag_id="break_mapping", start_date=datetime(2022, 3, 4)) as dag:

    @task
    def add_one(x: int):
        return x + 1

    @task
    def say_hi():
        print("Hi")

    @task
    def say_bye():
        print("Bye")

    added_values = add_one.expand(x=[])
    added_more_values = add_one.expand(x=[])
    added_more_more_values = add_one.expand(x=[])
    say_hi() >> say_bye() >> added_values
    added_values >> added_more_values >> added_more_more_values
```

### Operating System

Debian Bullseye

### Versions of Apache Airflow Providers

_No response_

### Deployment

Astronomer

### 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)

with dag_maker(session=session, dag_id="test"):
        task = BaseOperator(task_id="task_1")
    dr = DagRun(dag_id="test", run_id="test", run_type=DagRunType.MANUAL)
    ti0 = TI(task=task, run_id=dr.run_id, map_index=0, state=TaskInstanceState.SUCCESS)
    ti1 = TI(task=task, run_id=dr.run_id, map_index=1, state=None)
    ti2 = TI(task=task, run_id=dr.run_id, map_index=2, state=TaskInstanceState.SUCCESS)
    session.add_all((dr, ti0, ti1, ti2))
    session.flush()
    assert dr.schedule_tis((ti1,), session=session) == 1
    session.refresh(ti0)
    session.refresh(ti1)
    session.refresh(ti2)
    assert ti0.state == TaskInstanceState.SUCCESS
    assert ti1.state == TaskInstanceState.SCHEDULED
    assert ti2.state == TaskInstanceState.SUCCESS
def test_mapped_expand_kwargs(dag_maker):
    with dag_maker():
        @task
        def task_0():
            return {"arg1": "a", "arg2": "b"}
        @task
        def task_1(args_0):
            return [args_0, {"arg1": "y"}, {"arg2": "z"}]
        args_0 = task_0()
        args_list = task_1(args_0=args_0)
        MockOperator.partial(task_id="task_2").expand_kwargs(args_list)
        MockOperator.partial(task_id="task_3").expand_kwargs(