Something about the way we write concurrent programs has always felt wrong to me. When I pick up a new language and look at its concurrency model I get the same uneasy feeling. The APIs change, the terminology changes, but the underlying patterns look strangely familiar.
Москвичей предупредили о резком похолодании09:45。业内人士推荐PDF资料作为进阶阅读
The chancellor’s statement offered little new on tax or spending, but readers voiced concerns about rising costs，推荐阅读体育直播获取更多信息
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.，更多细节参见PDF资料
США примут дополнительные меры для остановки роста цен на нефть на фоне боевых действий на Ближнем Востоке. Об этом заявил американский президент Дональд Трамп, его цитирует ТАСС,.