> Text generated by an LM is not grounded in communicative intent

This means exactly that no representation should exist in the activation states about what the model wants to tell, and there must be only a single token probabilistic inference at play.

Also their model requires the contrary, too: that the model does not know, semantically, what the query really means.

Stochastic Parrot has a scientific meaning, and just only observing the function of the models, it is quite evident that they were very wrong, but now we have stong evidence (via probing) that also the sentence you quoted is not correct, since the model knows the idea to express also in general terms, and features about things it is going to say much later activates a lot of tokens earlier, including conceptual features that are relevant later in the sentence / concept expressed.

You are doing the big error that is common to do in this context of extending the stochastic parrot to a non scientifically isolated model that can be made large enough to accomodate any evidence arriving from new generations of models. The stochastic parrot does not understand the query nor is trying to reply to you in any way, it just exploits a probabilistic link among the context window and the next word. This link can be more complex than a Markov chain but must be of the same kind: lacking understanding whatsoever and communication intent (no representation of the concept / sentences that are required to reply correctly). How it is possible to believe in this, today? And, check yourself what the top AI scientists today believe about the correctness of the stochastic parrot hypothesis.