WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency

arXiv cs.AI · 18 hours ago

WaterMoE proposes a watermarking technique for Mixture-of-Experts language models that embeds watermarking signals through controlled perturbation in the expert selection process rather than as post-processing. The method achieves negligible quality degradation with only 1% additional inference latency and up to 4× speedup compared to existing watermarking methods across various generation tasks. This enables practical deployment of watermarking in latency-critical systems while maintaining model fidelity.