Paper

GridPE: A Grid Cell-Inspired Unified Position Embedding for Arbitrary-Dimensional Spaces

arXiv:2406.07049v3 Announce Type: replace-cross Abstract: Understanding spatial relationships across all dimensions is fundamental for intelligent systems. However, existing positional embeddings, such as Rotary Positional Embedding (RoPE), lack theoretical guarantees for high-dimensional spatiotemporal tasks like video understanding and robotic navigation. Inspired by the hexagonal periodic coding of grid cells in mammalian spatial cognition, we propose GridPE -- a novel positional embedding framework that integrates computational neuroscience principles with harmonic analysis. Our approach…

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