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LLMs possess shared internal 'preference vector' across personas

By PulseAugur Editorial · [1 sources] ·

Researchers have identified a shared internal 'preference vector' within large language models that influences their behavior across different personas. By training probes on activation data from Gemma-3-27B and Qwen-3.5-122B, they found this vector tracks and can even control the model's task and output choices. This representation appears to be largely consistent, even when the model adopts contrasting personas like a helpful assistant versus an 'evil' one. AI

IMPACT Identifies a shared internal mechanism for persona-dependent preferences in LLMs, suggesting potential for more nuanced control and understanding of model behavior.

RANK_REASON Academic paper detailing a new finding about internal model representations. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLMs possess shared internal 'preference vector' across personas

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Academic paper detailing a new finding about internal model representations. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Patrick Butlin ·

    Probing Persona-Dependent Preferences in Language Models

    Large language models (LLMs) can be said to have preferences: they reliably pick certain tasks and outputs over others, and preferences shaped by post-training and system prompts appear to shape much of their behaviour. But models can also adopt different personas which have radi…

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