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Found 9 papers, 9 papers with code
Comparative Evaluation of Label-Agnostic Selection Bias in Multilingual Hate Speech Datasets
Work on bias in hate speech typically aims to improve classification performance while relatively overlooking the quality of the data.
SemEval-2024 Task 1: Semantic Textual Relatedness for African and Asian Languages
We present the first shared task on Semantic Textual Relatedness (STR).
SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 14 Languages
Exploring and quantifying semantic relatedness is central to representing language.
The Intended Uses of Automated Fact-Checking Artefacts: Why, How and Who
Automated fact-checking is often presented as an epistemic tool that fact-checkers, social media consumers, and other stakeholders can use to fight misinformation.
SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)
We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at https://github. com/afrisenti-semeval/afrisent-semeval-2023.
AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages
These include 75 languages with at least one million speakers each.
Varifocal Question Generation for Fact-checking
Our method outperforms previous work on a fact-checking question generation dataset on a wide range of automatic evaluation metrics.
Probing Toxic Content in Large Pre-Trained Language Models
Large pre-trained language models (PTLMs) have been shown to carry biases towards different social groups which leads to the reproduction of stereotypical and toxic content by major NLP systems.
Multilingual and Multi-Aspect Hate Speech Analysis
Current research on hate speech analysis is typically oriented towards monolingual and single classification tasks.
