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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.17137381 |
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Table of Contents:
- <p>This deposit accompanies two complementary documents that together formalize and operationalize a new framework for attention mechanisms. The first document develops the theoretical foundation, introducing operator-theoretic, multi-scale, and neural-symbolic generalizations of self-attention. Key contributions include renormalisation-group attention flows, adaptive interpolation between vector-based and symbolic affinities, product-of-experts gating, entropy-based token budgeting, and prime-indexed positional encodings. The second document provides an operational addendum, translating these theoretical advances into precise, testable specifications suitable for deterministic software implementations. It details invariants, edge-case handling, and verification protocols, ensuring robustness, safety, and reproducibility. Together, the works extend the classical affinity-matrix paradigm, offering a mathematically principled and scalable approach to efficient and expressive neural attention.</p>