This is great! To answer your question specifically, it’s extremely useful for the team not to just know what evaluation metrics (e.g., mAP) are useful to the community, but also what tasks (or task types) the community wants to evaluate their models on, that use that metric.
This allows the team to

have a concrete benchmark to test the metric computation implementation and finetune performance (parallelization of compute, resource usage, etc.)
possibly easily develop an example to showcase the new metric’s availability in TFMA/TFDV

Many teams using TFX will have their own proprietary datasets that you can’t share with us. But it would be really useful to know, which public tasks [1] map most closely to ones the community is interested in.
[1] https://paperswithcode.com/area/computer-vision 1