### Apache Airflow version

2.4.3, 2.5.0

### What happened

when use output from task decorator as parameter (external_task_ids) in ExternalTaskSensor, it show up this log:

```
Broken DAG: [+++++/airflow/dags/TEST_NEW_PIPELINE.py] Traceback (most recent call last):
  File "+++++/env3.10.5/lib/python3.10/site-packages/airflow/models/baseoperator.py", line 408, in apply_defaults
    result = func(self, **kwargs, default_args=default_args)
  File "+++++/env3.10.5/lib/python3.10/site-packages/airflow/sensors/external_task.py", line 164, in __init__
    if external_task_ids and len(external_task_ids) > len(set(external_task_ids)):
TypeError: object of type 'PlainXComArg' has no len()
```

note: +++++ is just a mask for irrelevant information.

### What you think should happen instead

this document https://airflow.apache.org/docs/apache-airflow/stable/tutorial/taskflow.html
show that we can use it without any warning, note about it.

found relative problem in [https://github.com/apache/airflow/issues/27328](url)
should move all the check in __\_\_init\_\___ into __poke__ method.

### How to reproduce

```
from airflow.decorators import dag, task
from airflow.operators.python import get_current_context

from airflow.sensors.external_task import ExternalTaskSensor
from datetime import datetime

configure = {"dag_id": "test_new_skeleton",
                    "schedule": None,
                    "start_date": datetime(2022,1,1),
}

@task
def preprocess_dependency() -> list:
    return ["random-task-name"]

@dag(**configure)
def pipeline(): 
    t_preprocess = preprocess_dependency()
    task_dependency = ExternalTaskSensor(task_id=f"Check_Dependency",
                                         external_dag_id='random-dag-name-that-exist',
                                         external_task_ids=t_preprocess ,
                                         poke_interval=60,
                                         mode="reschedule",
                                         timeout=172800,
                                         allowed_states=['success'],
                                         failed_states=['failed', 'skipped'],
                                         check_existence=True,)


dag = pipeline()
```


### Operating System

REHL 7

### Versions of Apache Airflow Providers

_No response_

### Deployment

Virtualenv installation

### 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)

"""
    Use this operator to indicate that a task on a different DAG depends on this task.
    When this task is cleared with "Recursive" selected, Airflow will clear the task on
    the other DAG and its downstream tasks recursively. Transitive dependencies are followed
    until the recursion_depth is reached.
    :param external_dag_id: The dag_id that contains the dependent task that needs to be cleared.
    :param external_task_id: The task_id of the dependent task that needs to be cleared.
    :param execution_date: The logical date of the dependent task execution that needs to be cleared.
    :param recursion_depth: The maximum level of transitive dependencies allowed. Default is 10.
        This is mostly used for preventing cyclic dependencies. It is fine to increase
        this number if necessary. However, too many levels of transitive dependencies will make
        it slower to clear tasks in the web UI.
    """
    template_fields = ["external_dag_id", "external_task_id", "execution_date"]
    ui_color = "#19647e"
    operator_extra_links = [ExternalDagLink()]
    
    __serialized_fields: frozenset[str] | None = None
    def __init__(