"Or consider pipeTo(). Each chunk passes through a full Promise chain: read, write, check backpressure, repeat. An {value, done} result object is allocated per read. Error propagation creates additional Promise branches.
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.，推荐阅读新收录的资料获取更多信息
。关于这个话题，新收录的资料提供了深入分析
The same lifecycle works from C — use --link host.c instead:。新收录的资料对此有专业解读
今年是“十五五”开局之年。贵州坚持以文塑旅、以旅彰文，围绕“资源、客源、服务”三大要素，深入实施旅游产业化“四大行动”，将文旅产业作为重要支柱产业进行系统布局，奋力打造“多彩贵州”文旅新品牌，不断推动旅游业发展迈向更高水平。
2026年主流生成式AI工具与创收路径分析