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#logic-gates News & Analysis

2 articles tagged with #logic-gates. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles
AIBullisharXiv – CS AI · Mar 36/107
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Polynomial Surrogate Training for Differentiable Ternary Logic Gate Networks

Researchers introduce Polynomial Surrogate Training (PST) to enable differentiable ternary logic gate networks, reducing parameters by 2,187x while maintaining performance. The method extends beyond binary logic gates to ternary systems with an UNKNOWN state for uncertainty handling, training 2-3x faster than binary networks.

AINeutralarXiv – CS AI · Mar 175/10
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Align Forward, Adapt Backward: Closing the Discretization Gap in Logic Gate Networks

Researchers propose CAGE (Confidence-Adaptive Gradient Estimation) to solve the training-inference mismatch problem in neural networks that use soft mixtures during training but hard selection during inference. The method achieves over 98% accuracy on MNIST with zero selection gap, significantly outperforming existing approaches like Gumbel-ST which suffers accuracy collapse.