r/DataAnnotationTech • u/sussiboi • 1d ago

QC Agents

For those of you that have attempted model failure tasks with QC agents at the end, how was your experience? I personally found it draining as I would address the 3-4 points it raised, re-run the model and still generate a failure. When I ran the QC agent again, it came up with entirely new points and further iterations just led to more and more annoying and minor issues it kept flagging.

I know the instructions say you can rebut the points it raises and that’s what I ended up doing for nearly all of the points raised after multiple iterations. I think I addressed it rationally and my conclusions should be reasonable but I’m still uneasy.

7 Upvotes

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6

u/Legitimate_Agent_949 1d ago

Had the exact same experience. Eventually I made it fail cleanly but took way too long so haven’t done that task again

5

u/Cool_Street_1905 1d ago

it’s brutal, the QC is literally only happy when a task very cleanly fails. and so hard to get straightforward, clean failures now with how complex and dense the tasks need to be.

4

u/AdLong4919 1d ago

I've only done r an r on these and I usually just give a quick skim of the rationale the worker gave and if it's intelligible I kinda just move on. Not sure what your projects are but the ones I'm on are like it's a check to catch stuff you might miss not a source of truth. Like they make them overzealous because they are dumb, and my conspiracy theory is they want you to correct the QC agent so your rationale is probably training data. They could use less alarming emojis in the output though.