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arXiv · 2402.05526

Buffer Overflow in Mixture of Experts

Jamie Hayes·Ilia Shumailov·Itay Yona
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Abstract

Mixture of Experts (MoE) has become a key ingredient for scaling large foundation models while keeping inference costs steady. We show that expert routing strategies that have cross-batch dependencies are vulnerable to attacks. Malicious queries can be sent to a model and can affect a model's output on other benign queries if they are grouped in the same batch. We demonstrate this via a proof-of-concept attack in a toy experimental setting.

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Jamie Hayes, Ilia Shumailov, Itay Yona. 2024-02-08. Buffer Overflow in Mixture of Experts. https://arxiv.org/abs/2402.05526

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