### Description

Replace the existing selects with multi-selects that allow you to filter multiple DAG run states and types at the same time, somewhat similar to my prototype:

![image](https://github.com/apache/airflow/assets/1842905/c4ec0793-1ccb-417d-989c-781997416f97)


### Use case/motivation

I'm not sure if it is just me, but sometimes I wish I was able to show multiple DAG run states, especially `running` and `failed`, at the same time. 
This would be especially helpful for busy DAGs on which I want to clear a few failed runs. Without the multi-select, if I switch from `failed` to `running` DAG runs, I need to orient myself again to find the run I just cleared (assuming there are lots of other running DAG runs). _With_ the multi-select, the DAG run I just cleared stays in the same spot and I can check the logs, while clearing some other failed runs.

I'm not sure we need a multi-select for DAG run types as well. I'd tend to say no, but maybe someone else has a use-case for that.

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] 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)

self, task_instances: list[TaskInstance], session: Session, clear_downstream: bool = False
    ) -> tuple[int, int]:
        """
        Clear task instances, optionally including their downstream dependencies.
        :param task_instances: list of TIs to clear
        :param clear_downstream: should downstream task instances be cleared as well?
        :return: a tuple with:
            - count of cleared task instances actually selected by the user
            - count of downstream task instances that were additionally cleared
        """
        cleared_tis_count = 0
        cleared_downstream_tis_count = 0
        
        tis_grouped_by_dag_id = itertools.groupby(task_instances, lambda ti: ti.dag_id)
        for dag_id, dag_tis in tis_grouped_by_dag_id:
            dag = get_airflow_app().dag_bag.get_dag(dag_id)
            tis_to_clear = list(dag_tis)
            downstream_tis_to_clear = []
            if clear_downstream:
                tis_to_clear_grouped_by_dag_run = itertools.groupby(tis_to_clear, lambda ti: ti.dag_run)
                for dag_run, dag_run_tis in tis_to_clear_grouped_by_dag_run:
                    
                    
                    task_ids_to_clear = [ti.task_id for ti in dag_run_tis]
                    partial_dag = dag.partial_subset(
                        task_ids_or_regex=task_ids_to_clear, include_downstream=True, include_upstream=False
                    )
                    downstream_task_ids_to_clear = [
                        task_id for task_id in partial_dag.task_dict if task_id not in task_ids_to_clear
                    ]