I had the same question. I think that could be answered by using the predicted activation, but I don't see that in the paper.

That is, rather than just translate activation to text, then text to activation, that final activation could then be applied to the neural network, and it would be allowed to continue running from there.

If it kept running in a similar way, that would show that the predicted activation is close enough to the original one. Which would add some confidence here.

But a lot better would be to then do experiments with altered text. That is, if the text said "this is true" and it was changed to "this is false", and that intervention led to the final output implying it was false, that would be very interesting.

This seems obvious but I don't see it mentioned as a future direction there, so maybe there is an obvious reason it can't work.