Sometimes less is more: Investigating inductive biases of MLPs and Transformers on noisy k-parity features
Read the original at arxiv.org→arXiv:2610.37976v1 Announce Type: new Abstract: We empirically investigate how MLPs and Transformers differ when trained on data sets containing one or more features encoded by noisy k-parity. Noisy k-parity gives...
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- Oct 30, 04:00 UTC arXiv cs.LG lead source Sometimes less is more: Investigating inductive biases of MLPs and Transformers on noisy k-parity features