Recurrent neural networks spontaneously model partners during collaboration — without specialised architectures — but only when partner-specific adaptation improves task performance.

We present a novel counterfactual regularization algorithm to train partner-aware collaborator LLM agents that can discriminate helpful vs. unhelpful information in collaborator utterances