LGAINov 11, 2025

Clifford Algebraic Rotor Embeddings : Maybe embeddings should start to CARE

arXiv:2511.11665v12 citationsh-index: 2
Originality Incremental advance
AI Analysis

This work addresses a technical bottleneck in positional encoding for machine learning models, offering a novel mathematical framework that is incremental but extends existing methods.

The paper tackles the problem of extending Rotary Positional Embeddings (RoPE) to higher dimensions while preserving shift-equivariance, by proposing Clifford Algebraic Rotary Embeddings (CARE) as a generalization using geometric algebra, which enables rotary embeddings in arbitrary dimensions and encodes positional information in multivectors.

Rotary Positional Embeddings (RoPE) have demonstrated exceptional performance as a positional encoding method, consistently outperforming their baselines. While recent work has sought to extend RoPE to higher-dimensional inputs, many such extensions are non-commutative, thereby forfeiting RoPE's shift-equivariance property. Spherical RoPE is one such non-commutative variant, motivated by the idea of rotating embedding vectors on spheres rather than circles. However, spherical rotations are inherently non-commutative, making the choice of rotation sequence ambiguous. In this work, we explore a quaternion-based approach -- Quaternion Rotary Embeddings (QuatRo) -- in place of Euler angles, leveraging quaternions' ability to represent 3D rotations to parameterize the axes of rotation. We show Mixed RoPE and Spherical RoPE to be special cases of QuatRo. Further, we propose a generalization of QuatRo to Clifford Algebraic Rotary Embeddings (CARE) using geometric algebra. Viewing quaternions as the even subalgebra of Cl(3,0,0), we extend the notion of rotary embeddings from quaternions to Clifford rotors acting on multivectors. This formulation enables two key generalizations: (1) extending rotary embeddings to arbitrary dimensions, and (2) encoding positional information in multivectors of multiple grades, not just vectors. We present preliminary experiments comparing spherical, quaternion, and Clifford-based rotary embeddings.

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