Zheng-Hang Li

Reinforcement learning-guided archival question answering with adaptive curriculum learning

A reinforcement learning-guided question answering model specifically designed for archival question answering scenarios, incorporating a hierarchical reward mechanism that evaluates answer quality across multiple dimensions including factual accuracy, semantic relevance, and provenance clarity is proposed.