Researchers developed a method to instill Big-5 OCEAN personality traits into large language models across multiple model families (Llama 3.1, Qwen3, Gemma3) at sizes 4B–32B parameters using a modified Open Character Training pipeline and low-rank adapters (LoRAs). They demonstrated that these trait-encoding components can be scaled, inverted, and combined using simple weight matrix arithmetic to amplify, suppress, and blend different behavioral traits.
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