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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2025年底，《桃源村日志》报名参加Steam的“古装游戏节”活动，当天方块便主动联系了她们，第二天登门拜访，不到两周双方完成签约。，推荐阅读体育直播获取更多信息
As schools begin to introduce AI literacy courses for their students, Horvath said there are ways for learners to develop a balanced relationship with the emerging technology. Edtech advocates have confused curriculum with pedagogy, he suggested. While curriculum refers to what is taught, pedagogy is how that material is taught. Instead of teaching students about computers—where technology would be in the curriculum—edtech has become about teaching a subject matter through computers, a pedagogy that has shown it’s not effective.，这一点在体育直播中也有详细论述
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