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Found 4 papers, 0 papers with code
Advancing Ante-Hoc Explainable Models through Generative Adversarial Networks
This paper presents a novel concept learning framework for enhancing model interpretability and performance in visual classification tasks.
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach
Estimating the transferability of publicly available pretrained models to a target task has assumed an important place for transfer learning tasks in recent years.
Model-Agnostic Meta-Learning for Multilingual Hate Speech Detection
However, most of these studies are limited to detecting hate speech only in English, neglecting the bulk of hateful content that is generated in other languages, particularly in low-resource languages.
Handling Bias in Toxic Speech Detection: A Survey
While reducing toxicity on online platforms continues to be an active area of research, a systematic study of various biases and their mitigation strategies will help the research community produce robust and fair models.
