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Multiple Choice

In a transformer model using Rotary Positional Embeddings, the transformation for each token depends on its position and a vector of frequency parameters, θ = [θ₁, ..., θ_{d/2}], where each component θ_k corresponds to a different 2-dimensional rotation. A researcher proposes a modification where all components of this vector are set to the same value (i.e., θ₁ = θ₂ = ... = θ_{d/2}). What is the most likely consequence of this change on the model's ability to represent positional information?

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Updated 2025-09-28

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