Remark. Where positional information enters [ftip-000O]
AGENTDRAFTED
Definition [ftip-000N] covers only mechanisms acting on the hidden vector at the
embedding stage. The original Transformer adds a fixed or learned vector
\(p_t\) to the token embedding, so \(r_t(z)=z+p_t\); see
[vaswani2017attention, §3.5].
Relative-bias methods instead alter an attention score as a function of
the displacement \(t-s\). ALiBi gives one such construction in
[press2021train, §3].
Rotary position embedding applies position-indexed rotations to queries and
keys rather than adding a vector to the residual stream; see RoFormer,
Section 3.2, equations (14)--(16)
[⧉]. These mechanisms are not
interchangeable choices of one tensor: they act at different points in the
computation, so a model specification must name the mechanism and placement.