Neural-IC separates embedding inequalities from capacity bounds in query-separated computations, with one-bit RAC benchmarks and CHSH-layer stability selecting the Tsirelson threshold for quantum enhancements.
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PAM, a complex-valued associative memory model, exhibits steeper power-law scaling in loss and perplexity than a matched real-valued baseline when trained on WikiText-103 from 5M to 100M parameters.
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Neural Information Causality
Neural-IC separates embedding inequalities from capacity bounds in query-separated computations, with one-bit RAC benchmarks and CHSH-layer stability selecting the Tsirelson threshold for quantum enhancements.
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Phase-Associative Memory: Sequence Modeling in Complex Hilbert Space
PAM, a complex-valued associative memory model, exhibits steeper power-law scaling in loss and perplexity than a matched real-valued baseline when trained on WikiText-103 from 5M to 100M parameters.