3 citations · 3 across the 5 of their papers we have counts for
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cs.NE2026
Event-Driven Language Models with Sparse Neural Activity for Neuromorphic Hardware
Simon Richter, Ruhai Lin, Jason Yik +4
Inference with transformer-based large language models (LLMs) is often limited by the memory-bound KV cache and quadratic attention cost. State-space models (SSMs) mitigate this th…
cs.NE2025★ 3 cited
NeuroMorse: A Temporally Structured Dataset For Neuromorphic Computing
Ben Walters, Yeshwanth Bethi, Taylor Kergan +5
Neuromorphic engineering aims to advance computing by mimicking the brain's efficient processing, where data is encoded as asynchronous temporal events. This eliminates the need fo…