### 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)

return x + 1
        @dag.task
        def say_hi():
            print("Hi")
        added_values = add_one.expand(x=[])
        added_more_values = add_one.expand(x=[])
        say_hi() >> added_values
        added_values >> added_more_values
    dr = dag_maker.create_dagrun()
    session = dag_maker.session
    tis = {ti.task_id: ti for ti in dr.task_instances}
    tis["say_hi"].state = TaskInstanceState.SUCCESS
    session.flush()
    dr.update_state(session=session)
    assert dr.state == DagRunState.SUCCESS
    assert tis["add_one__1"].state == TaskInstanceState.SKIPPED
def test_schedulable_task_exist_when_rerun_removed_upstream_mapped_task(session, dag_maker):
    from airflow.decorators import task
    @task
    def do_something(i):
        return 1
    @task
    def do_something_else(i):
        return 1
    with dag_maker():
        nums = do_something.expand(i=[i + 1 for i in range(5)])
        do_something_else.expand(i=nums)
    dr = dag_maker.create_dagrun()
    ti = dr.get_task_instance("do_something_else", session=session)
    ti.map_index = 0