The classic Bayer or ‘dispersed-dot’ pattern arranges threshold values in an attempt to optimise information transfer and minimise noise[7]. The matrix dimensions are typically a power of two. The following values describe an 8×8 matrix:
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，这一点在搜狗输入法2026中也有详细论述
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.
When I first transitioned to GrapheneOS I gave in depth write ups on the apps I kept and the apps I got rid of . This was my first time trying to be intentional about my phone usage. Back then I broke my apps down into five buckets:
（十一）泄露办理治安案件过程中的工作秘密或者其他依法应当保密的信息的；