Enhancing Transformers with Polarity Encoders to Detect Sarcasm
A polarity-sensitive transformer model that explicitly incorporates sentiment data in representation learning is presented, indicating that embedding-level sentiment improvement offers a sound theoretical and practical guideline in the process of expanding sarcasm detection beyond implicit contextual modeling.