The MLE-Morpho-Logic-Engine is built on several landmark papers in neural computing and vector logic:
: It avoids traditional training data and GPU-heavy gradients. harry00
If you are looking for "long papers" or theoretical foundations related to this specific work, you should focus on the core research papers that Harry00 cites as the engine's theoretical basis. Theoretical Foundations of Harry00's MLE harry00
: This foundational paper introduces a mathematical model for human long-term memory using high-dimensional binary vectors and Hamming distance for addressing. harry00
: This paper outlines the "Map-Bind-Bundle" framework, which allows for the manipulation of symbolic structures within a continuous vector space—key to the MLE's ability to perform logical operations.
: Unlike autoregressive LLMs, it uses energy minimization to "reason" through problems.