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RoPE: How 2D Rotations Solved Transformer Long-Context
Why 2D Rotations Solved Transformer Long-Context: A Mechanics-First Look at RoPE
Attention requires two things from positional encodings:
Relative Distance Sensitivity: Token
i
attending to Token
j
should care primarily about how far apart they are (
i − j
), not where they sit globally in the context window.
Feature Preservation: Injecting position information must not destroy or mangle the semantic embedding ...
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