### 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)

print(repr(args))
        PythonOperator.partial(
            task_id="consumer",
            trigger_rule=trigger_rule,
            python_callable=consumer,
        ).expand(op_args=make_list())
    dr = dag_maker.create_dagrun()
    _, make_list_ti = sorted(dr.task_instances, key=lambda ti: ti.task_id)
    make_list_ti.state = TaskInstanceState.FAILED
    session.flush()
    tis, _ = dr.update_state(execute_callbacks=False, session=session)
    assert tis == []
    tis = sorted(dr.task_instances, key=lambda ti: ti.task_id)
    assert sorted((ti.task_id, ti.map_index, ti.state) for ti in tis) == [
        ("consumer", -1, TaskInstanceState.UPSTREAM_FAILED),
        ("make_list", -1, TaskInstanceState.FAILED),
    ]
    
    
    tis, _ = dr.update_state(execute_callbacks=False, session=session)
    assert tis == []
    assert dr.state == DagRunState.FAILED
def test_mapped_task_all_finish_before_downstream(dag_maker, session):
    result = None
    with dag_maker(session=session) as dag:
        @dag.task
        def make_list():
            return [1, 2]
        @dag.task
        def double(value):