Mmorgan-ML/Neuromodulatory-Control-Networks
Neuromodulatory Control Networks (NCNs), a novel LLM architectural modification inspired by the neuromodulatory systems in the vertebrate brain.
This project offers a new way to build Large Language Models (LLMs) that can dynamically adjust how they process information. It takes contextual cues, task demands, or operational modes as input, and then outputs dynamic 'modulatory signals' that influence the LLM's computational properties, such as attention and signal strength. This is for AI researchers and machine learning engineers who want to develop more adaptive and efficient language models.
Use this if you are developing LLMs and need them to adapt their processing strategy dynamically based on context or task, rather than having static processing mechanisms.
Not ideal if you are looking for a pre-trained, production-ready LLM for direct application without needing to delve into architectural modifications.
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Python
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Last pushed
Dec 11, 2025
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