Abstract
Since the dawn of Transformer-based models, the trade-off between transparency and accuracy has been a topical issue in the NLP community. Working towards ethical and transparent automated content moderation (ACM), my goal is to find where it is still relevant to implement linguistic expertise. I show that transparent statistical models based on linguistic knowledge can still be competitive, while linguistic features have many other useful applications.
Keywords
- Natural Language Processing: NLP: Interpretability and analysis of models for NLP
- AI Ethics, Trust, Fairness: ETF: Explainability and interpretability
- Natural Language Processing: NLP: Applications
