LANE: Advancing Word Sense Disambiguation with Adversarial Examples

This research explores a novel approach to Word Sense Disambiguation (WSD) using adversarial examples, which is a significant contribution to the field. The use of 'Lexical Adversarial Negative Examples' offers a potentially powerful method for improving the accuracy and robustness of WSD models.

• •Focuses on improving Word Sense Disambiguation (WSD).
• •Employs adversarial examples for enhanced model performance.
• •Potentially increases the robustness of WSD models.