On a benchmark where models train on Fourier components and test on their sums, patch-based Transformers and residual MLP architectures show the strongest compositional generalization, while most standard transformers and linear models fail.
Physics of language models: Part 3.2, knowledge manipula- tion, 2023
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Investigating Compositional Reasoning in Time Series Foundation Models
On a benchmark where models train on Fourier components and test on their sums, patch-based Transformers and residual MLP architectures show the strongest compositional generalization, while most standard transformers and linear models fail.