A research team from UC Davis, Microsoft Research and Johns Hopkins University extends work on training massive amounts of linguistic data to reveal the grammatical structures in their representations to the domain of mathematical reasoning, showing that both the standard transformer and the TP-Transformer can compose the meanings of mathematical symbols based on their structured relationships.

Here is a quick read: Study Shows Transformers Possess the Compositionality Power for Mathematical Reasoning.

The paper Compositional Processing Emerges in Neural Networks Solving Math Problems is on arXiv.

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