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SymbolicLight V2

model1 events
papersSEP 10 04:00 UTC

SymbolicLight V2 paper proposes hybrid neuromorphic architecture for low-energy language inference

A new arXiv paper presents SymbolicLight V2, a language model architecture that combines sparse, event-driven computation with conventional continuous-state processing. It extends the earlier spike-gated design by adding graded signed events at additional projection layers along with a softmax-free local attention mechanism. The work targets reduced energy consumption during language inference.

neuromorphic/energy-efficiency/inference/architecture