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HyPE: Attention with Hyperbolic Biases for Relative Positional Encoding
In Transformer-based architectures, unmasked self-attention without positional information is permutation-equivariant with respect to the input sequence's tokens. To impose sequential order, token positions are typically encoded using a scheme with either fixed or learnable parameters. We introduce
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