Feature Selection Boosts BERT for Hate Speech Detection
Published:Dec 1, 2025 19:11
•1 min read
•ArXiv
Analysis
This research explores enhancements to BERT for hate speech detection, a critical area in AI safety and online content moderation. The vocabulary augmentation aspect suggests an attempt to improve robustness against variations in language and slang.
Key Takeaways
- •Applies feature selection techniques to improve BERT's performance in hate speech detection.
- •Employs vocabulary augmentation to enhance the model's ability to recognize varied language.
- •Contributes to the ongoing effort of making AI systems safer and more reliable in content analysis.
Reference
“The study focuses on using Feature Selection and Vocabulary Augmentation with BERT to detect hate speech.”