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该论文提出福利感知偏好获取方法（WAPA），在有限人工反馈预算下，通过社会 welfare 目标来分配人工标注，以改善多元对齐中不同个体偏好的监督质量，实验证明仅获取 20% 人工标签即可恢复 75–86% 的效用差距。
The article examines whether Europe's social welfare model can withstand AI-driven job disruption, contrasting the EU's regulatory focus with Silicon Valley's proposals for universal basic income, while highlighting uncertainty about AI's actual impact on employment.
The article explores the r/almosthomeless subreddit, where people facing homelessness share support and resources, highlighting growing wealth inequality in the US.