Abstract
We propose a novel RoBERTa-based model, RoPPT, which introduces a
target-oriented parse tree structure in metaphor detection. Compared to
existing models, RoPPT focuses on semantically relevant information and
achieves the state-of-the-art on several main metaphor datasets. We also
compare our approach against several popular denoising and pruning methods,
demonstrating the effectiveness of our approach in context denoising. Our code
and dataset can be found at https://github.com/MajiBear000/RoPPT