This paper proposes a new representation learning framework -∆-learning, which can distill both discrimination and generalization knowledge for event detection.
two effective ∆-learning algorithms are proposed to distill discrimination and generalization knowledge independently, and a lexical gate mechanism is designed to fuse different knowledge adaptively.