TOWARDS THE ROBUST AND UNIVERSAL SEMANTIC REPRESENTATION FOR ACTION DESCRIPTION

Achieving a robust and universal semantic representation for action description remains the key challenge in natural language understanding. Current approaches often struggle to capture the subtlety of human actions, leading to inaccurate representations. To address this challenge, we propose new framework that leverages deep learning techniques to