Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection

6 May 2022

Papers citing "Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection"

4 / 4 papers shown

Title
Promoting Security and Trust on Social Networks: Explainable Cyberbullying Detection Using Large Language Models in a Stream-Based Machine Learning Framework Silvia García-Méndez Francisco de Arriba-Pérez 17 0 0 07 Apr 2025
InterroLang: Exploring NLP Models and Datasets through Dialogue-based Explanations Nils Feldhus Qianli Wang Tatiana Anikina Sahil Chopra Cennet Oguz Sebastian Möller 26 9 0 09 Oct 2023
Towards Procedural Fairness: Uncovering Biases in How a Toxic Language Classifier Uses Sentiment Information I. Nejadgholi Esma Balkir Kathleen C. Fraser S. Kiritchenko 23 3 0 19 Oct 2022
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models Esma Balkir S. Kiritchenko I. Nejadgholi Kathleen C. Fraser 16 36 0 08 Jun 2022