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JoeSzeles / neural-preference-learning

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Neural Preference Learning (NPL) is a novel architecture that gives LLM agents persistent, personal preferences by pairing them with a companion spiking neural network. Unlike RLHF (which is batch, pre-deployment, and population-level), NPL operates in real-time, learning from individual user feedback through natural language.

reinforcement-learning hebbian-learning preference-learning lif-neuron spiking-neural-network rlhf llm-agent openclaw brainjar
  • Updated Mar 16, 2026
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