On the Spatial Structure of Mixture-of-Experts in Transformers

Daniel Bershatsky; Ivan Oseledets

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arXiv · 2504.04444

On the Spatial Structure of Mixture-of-Experts in Transformers

Daniel Bershatsky·Ivan Oseledets

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Abstract

A common assumption is that MoE routers primarily leverage semantic features for expert selection. However, our study challenges this notion by demonstrating that positional token information also plays a crucial role in routing decisions. Through extensive empirical analysis, we provide evidence supporting this hypothesis, develop a phenomenological explanation of the observed behavior, and discuss practical implications for MoE-based architectures.

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Daniel Bershatsky, Ivan Oseledets. 2025-04-06. On the Spatial Structure of Mixture-of-Experts in Transformers. https://arxiv.org/abs/2504.04444

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