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Found 15 papers, 10 papers with code
AfroXLMR-Social: Adapting Pre-trained Language Models for African Languages Social Media Text
We explore a thorough analysis of domain and task adaptive continual pretraining approaches for low-resource African languages and a promising result is shown for the evaluated tasks.
Enhancing Multi-Label Emotion Analysis and Corresponding Intensities for Ethiopian Languages
As users express different emotions simultaneously in a single instance, annotating emotions in a multilabel setting such as the EthioEmo (Belay et al., 2025) dataset effectively captures this dynamic.
SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection
The data instances are multi-labeled into six emotional classes, with additional datasets in 11 languages annotated for emotion intensity.
AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages
These limitations are mainly due to the lack of high-quality data in the local languages and the failure to include local communities in the collection, annotation, and moderation processes.
Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding
The results show that accurate multi-label emotion classification is still insufficient even for high-resource languages such as English, and there is a large gap between the performance of high-resource and low-resource languages.
Multilingual and Explainable Text Detoxification with Parallel Corpora
Even with various regulations in place across countries and social media platforms (Government of India, 2021; European Parliament and Council of the European Union, 2022, digital abusive speech remains a significant issue.
BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages
To address this issue, we introduce BLEnD, a hand-crafted benchmark designed to evaluate LLMs' everyday knowledge across diverse cultures and languages.
Exploring Boundaries and Intensities in Offensive and Hate Speech: Unveiling the Complex Spectrum of Social Media Discourse
The prevalence of digital media and evolving sociopolitical dynamics have significantly amplified the dissemination of hateful content.
EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation
We open-source our multilingual language models, new benchmark datasets for various downstream tasks, and task-specific fine-tuned language models and discuss the performance of the models.
SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 13 Languages
Exploring and quantifying semantic relatedness is central to representing language and holds significant implications across various NLP tasks.
Natural Language Processing in Ethiopian Languages: Current State, Challenges, and Opportunities
This survey delves into the current state of natural language processing (NLP) for four Ethiopian languages: Amharic, Afaan Oromo, Tigrinya, and Wolaytta.
AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages
These include 75 languages with at least one million speakers each.
The Effect of Normalization for Bi-directional Amharic-English Neural Machine Translation
Machine translation (MT) is one of the main tasks in natural language processing whose objective is to translate texts automatically from one natural language to another.
Introducing various Semantic Models for Amharic: Experimentation and Evaluation with multiple Tasks and Datasets
We find that newly trained models perform better than pre-trained multilingual models.
Analysis of the Ethiopic Twitter Dataset for Abusive Speech in Amharic
Since several languages can be written using the Fidel script, we have used the existing Amharic, Tigrinya and Ge'ez corpora to retain only the Amharic tweets.
