### 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)

)
    def test_wait_for_downstream(self, session, prev_ti_state, is_ti_success):
        dag_id = "test_wait_for_downstream"
        dag = self.dagbag.get_dag(dag_id)
        upstream, downstream = dag.tasks
        
        
        dag_run_1 = self.create_dag_run(
            dag,
            execution_date=timezone.datetime(2016, 1, 1, 0, 0, 0),
            is_backfill=True,
            session=session,
        )
        dag_run_2 = self.create_dag_run(
            dag,
            execution_date=timezone.datetime(2016, 1, 2, 0, 0, 0),
            is_backfill=True,
            session=session,
        )
        prev_ti_downstream = TI(task=downstream, run_id=dag_run_1.run_id)
        ti = TI(task=upstream, run_id=dag_run_2.run_id)
        prev_ti = ti.get_previous_ti()
        prev_ti.set_state(TaskInstanceState.SUCCESS)
        assert prev_ti.state == TaskInstanceState.SUCCESS
        prev_ti_downstream.set_state(prev_ti_state)
        ti.set_state(TaskInstanceState.QUEUED)
        ti.run()
        assert (ti.state == TaskInstanceState.SUCCESS) == is_ti_success
    @pytest.mark.parametrize("state", [DagRunState.QUEUED, DagRunState.RUNNING])
    def test_next_dagruns_to_examine_only_unpaused(self, session, state):