How does dynamic hot neuron threshold adjustment in PowerInfer influence the alignment of LLaMA-70B outputs wi

Abstract

Abstract: Emerging research in Pluralistic Artificial Intelligence (AI) alignment seeks to address how intelligent systems can be designed and deployed in accordance with diverse human needs and values. We contribute to this pursuit with a dynamic approach for aligning AI with diverse and shifting user preferences through Multi Objective Reinforcement Learning (MORL), via post-learning policy selection adjustment. In this paper, we introduce the proposed framework for this approach, outline its anticipated advantages and assumptions, and discuss technical details about the implementation. We also examin

Research Question

How does dynamic hot neuron threshold adjustment in PowerInfer influence the alignment of LLaMA-70B outputs with human preferences in MBPP Python function synthesis tasks, measured by human evaluation scores?

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Provenance