Learning-To-Measure: In-Context Active Feature Acquisition 事件

Learning-To-Measure: In-Context Active Feature Acquisition arXiv:2510.12624v2 Announce Type: replace-cross Abstract: Active feature acquisition (AFA) is a sequential decision-making problem where the goal is to improve model performance for test instances by adaptively selecting which features to acquire. In practice, AFA methods often learn from retrospective data with systematic missingness in the features and limited task-specific labels. Most prior work addresses acquisition for a single pr