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On the Depth Scalability of Logic Gate Networks

An, Taegun et al.
arXiv (OAI Expanded) · Papers
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artificial-intelligencelogic-in-computer-sciencemachine-learning
Logic Gate Networks (LGNs) compute through compositions of Boolean operations, yet existing LGNs do not reliably benefit from increased depth. We identify two causes: optimization collapse and topology-induced degradation of output-specific credit that persists even after skip-biased initialization
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