>It's the amount of bad data relative to the overall dataset that matters,

Isn't that the opposite of the findings here? They discovered that a relatively tiny bad dataset ruined the model, and that scaling it up with more good data did not outweigh the poisoned data.

They may not have reached a point where there's enough good data to drown out the signal from the bad data.