They do not study how the population loss decreases during the first stage.

An overarching goal in machine learning is to build ageneralizable model with fewsamples.

Then each client alternately estimates its cluster labels and refines the model estimates based on FedAvg or FedProx.

In Step 9, PS{ j( j i,t)}kj=1 lie collaboration St. Inparticulari 2 H, define Yi,t = 1 m X

However, the task is challenging due to the noisy nature of fMRI signals and the intricate pattern of brain visual representations.

The PETL parameters are trained only on Task 1 (the'first-session') of a set of

December 5, 2025 Abstract We argue that language models (LMs) have strong potential as investigative tools for probing the distinction between possible and impossible natural languages and thus uncovering the inductive biases that support human language learning. We outline a phased research program in which LM architectures are iteratively refined to better discriminate between possible and impossible languages, supporting linking hypotheses to human cognition. Which conceivable linguistic systems are possible for humans to learn and use as natural languages? A complete answer to this question would yield profound insights into the human capacity for language. However, our tools for addressing the question are very limited.