Gradient Masters Tackle Bengali Hate Speech: Advancing Low-Resource NLP
Published:Nov 23, 2025 07:29
•1 min read
•ArXiv
Analysis
This research paper focuses on a critical challenge: detecting hate speech in a low-resource language. The use of ensemble-based adversarial training is a promising approach to improve model robustness and accuracy in this context.
Key Takeaways
- •The paper explores hate speech detection in Bengali, a low-resource language.
- •The methodology employs ensemble-based adversarial training.
- •The research contributes to improved NLP for under-resourced languages.
Reference
“The research focuses on the BLP-2025 Task 1, addressing hate speech detection.”