AI RESEARCH
StoicLLM: Preference Optimization for Philosophical Alignment in Small Language Models
arXiv CS.CL
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ArXi:2605.11483v1 Announce Type: new While large language models excel at factual adaptation, their ability to internalize nuanced philosophical frameworks under severe data constraints remains underexplored. We investigate this by specializing small LLMs on micro-datasets of foundational Stoic texts using preference optimization (ORPO, AlphaPO). Evaluated via a multi-model critic bank, our results show that just 300 high-fidelity examples can induce strong alignment with inward-facing Stoic virtues, closely approaching few-shot prompting while freeing the context window.