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Simon Richter

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#machine learning Preprint Aug 2026

Event-Driven Language Models with Sparse Neural Activity for Neuromorphic Hardware

This work introduces a method that induces sparse neural activity in heavily quantized linear-attention models with minimal performance loss, and positions sparse, quantized linear-attention models as a natural fit for deploying LLMs on event-driven multi-core platforms.

Simon Richter, Ruhai Lin, Jason Yik et al. · 0 citations