המרה של טקסט ארוך למאפיינים נבחרים: פיתוח תכונות בלוק-בלוק על ידי חיפוש תוכנה מבוצע

תקציר מקורי באנגליתarXiv:2610.12390v1 Announce Type: new Abstract: Industrial risk-control systems typically rely on structured-data models for efficient prediction, yet substantial valuable information remains embedded in unstructured long text. Extracting this information through manual feature engineering is labor-intensive, while requiring a large language model (LLM) to process every real-time input may not meet practical deployment requirements. To address this challenge, we propose LLM-BlockFE, an LLM-guided offline feature construction framework that converts long text into executable feature programs, thereby avoiding LLM calls during online inference. LLM-BlockFE constructs feature programs by incrementally appending immutable code blocks and evaluates candidate features using a downstream model. T