无论波斯以前多阔气，伊斯兰教的先知穆罕默德是阿拉伯人，《古兰经》也是用阿拉伯语降示的。
Abstract:Humans shift between different personas depending on social context. Large Language Models (LLMs) demonstrate a similar flexibility in adopting different personas and behaviors. Existing approaches, however, typically adapt such behavior through external knowledge such as prompting, retrieval-augmented generation (RAG), or fine-tuning. We ask: do LLMs really need external context or parameters to adapt to different behaviors, or do they already have such knowledge embedded in their parameters? In this work, we show that LLMs already contain persona-specialized subnetworks in their parameter space. Using small calibration datasets, we identify distinct activation signatures associated with different personas. Guided by these statistics, we develop a masking strategy that isolates lightweight persona subnetworks. Building on the findings, we further discuss: how can we discover opposing subnetwork from the model that lead to binary-opposing personas, such as introvert-extrovert? To further enhance separation in binary opposition scenarios, we introduce a contrastive pruning strategy that identifies parameters responsible for the statistical divergence between opposing personas. Our method is entirely training-free and relies solely on the language model's existing parameter space. Across diverse evaluation settings, the resulting subnetworks exhibit significantly stronger persona alignment than baselines that require external knowledge while being more efficient. Our findings suggest that diverse human-like behaviors are not merely induced in LLMs, but are already embedded in their parameter space, pointing toward a new perspective on controllable and interpretable personalization in large language models.
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正在广东考察调研的习近平总书记走进柚子林，同乡亲们亲切交流，指出“发展乡村特色产业是推进乡村全面振兴的基础”，要求不断延伸产业链、增加附加值，带动更多农民群众增收致富。
（二）投放虚假的爆炸性、毒害性、放射性、腐蚀性物质或者传染病病原体等危险物质扰乱公共秩序的；
Kacper Rozanski operates Shadow Robot hands