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Found 46 papers, 17 papers with code
Question Answering Classification for Amharic Social Media Community Based Questions
Questions are posted in Amharic, English, or Amharic but in a Latin script.
Elvis vs. M. Jackson: Who has More Albums? Classification and Identification of Elements in Comparative Questions
Comparative Question Answering (cQA) is the task of providing concrete and accurate responses to queries such as: “Is Lyft cheaper than a regular taxi?” or “What makes a mortgage different from a regular loan?”.
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.
Pruning Literals for Highly Efficient Explainability at Word Level
Designing an explainable model becomes crucial now for Natural Language Processing(NLP) since most of the state-of-the-art machine learning models provide a limited explanation for the prediction.
Hate Speech Detection and Classification in Amharic Text with Deep Learning
To address this gap, we develop Amharic hate speech data and SBi-LSTM deep learning model that can detect and classify text into four categories of hate speech: racial, religious, gender, and non-hate speech.
Demarked: A Strategy for Enhanced Abusive Speech Moderation through Counterspeech, Detoxification, and Message Management
Despite regulations imposed by nations and social media platforms, such as recent EU regulations targeting digital violence, abusive content persists as a significant challenge.
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.
SemEval-2024 Task 1: Semantic Textual Relatedness for African and Asian Languages
We present the first shared task on Semantic Textual Relatedness (STR).
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.
Walia-LLM: Enhancing Amharic-LLaMA by Integrating Task-Specific and Generative Datasets
We compile an Amharic instruction fine-tuning dataset and fine-tuned LLaMA-2-Amharic model.
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.
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.
ARDIAS: AI-Enhanced Research Management, Discovery, and Advisory System
In this work, we present ARDIAS, a web-based application that aims to provide researchers with a full suite of discovery and collaboration tools.
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.
SCoT: Sense Clustering over Time: a tool for the analysis of lexical change
There are two main approaches to the exploration of dynamic networks: the discrete one compares a series of clustered graphs from separate points in time.
How Hateful are Movies? A Study and Prediction on Movie Subtitles
Hence, we show that transfer learning from the social media domain is efficacious in classifying hate and offensive speech in movies through subtitles.
ActiveAnno: General-Purpose Document-Level Annotation Tool with Active Learning Integration
ActiveAnno is built with extensible design and easy deployment in mind, all to enable users to perform annotation tasks with high efficiency and high-quality annotation results.
Word Complexity is in the Eye of the Beholder
Lexical complexity is a highly subjective notion, yet this factor is often neglected in lexical simplification and readability systems which use a {''}one-size-fits-all{''} approach.
MasakhaNER: Named Entity Recognition for African Languages
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages, bringing together a variety of stakeholders.
HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection
We also observe that models, which utilize the human rationales for training, perform better in reducing unintended bias towards target communities.
Ranked #3 on
Hate Speech Detection
on HateXplain
Exploring Amharic Sentiment Analysis from Social Media Texts: Building Annotation Tools and Classification Models
To advance the sentiment analysis research in Amharic and other related low-resource languages, we release the dataset, the annotation tool, source code, and models publicly under a permissive.
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.
UHH-LT at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language Detection
Fine-tuning of pre-trained transformer networks such as BERT yield state-of-the-art results for text classification tasks.
Automatic Compilation of Resources for Academic Writing and Evaluating with Informal Word Identification and Paraphrasing System
The aim is to build a writing aid system that automatically edits a text so that it better adheres to the academic style of writing.
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.
A Multilingual Information Extraction Pipeline for Investigative Journalism
We introduce an advanced information extraction pipeline to automatically process very large collections of unstructured textual data for the purpose of investigative journalism.
Demonstrating PAR4SEM - A Semantic Writing Aid with Adaptive Paraphrasing
In this paper, we present Par4Sem, a semantic writing aid tool based on adaptive paraphrasing.
New/s/leak 2.0 - Multilingual Information Extraction and Visualization for Investigative Journalism
Investigative journalism in recent years is confronted with two major challenges: 1) vast amounts of unstructured data originating from large text collections such as leaks or answers to Freedom of Information requests, and 2) multi-lingual data due to intensified global cooperation and communication in politics, business and civil society.
Par4Sim -- Adaptive Paraphrasing for Text Simplification
Learning from a real-world data stream and continuously updating the model without explicit supervision is a new challenge for NLP applications with machine learning components.
A Report on the Complex Word Identification Shared Task 2018
We report the findings of the second Complex Word Identification (CWI) shared task organized as part of the BEA workshop co-located with NAACL-HLT'2018.
CWIG3G2 - Complex Word Identification Task across Three Text Genres and Two User Groups
Complex word identification (CWI) is an important task in text accessibility.
Multilingual and Cross-Lingual Complex Word Identification
Complex Word Identification (CWI) is an important task in lexical simplification and text accessibility.
Entity-Centric Information Access with Human in the Loop for the Biomedical Domain
In this paper, we describe the concept of entity-centric information access for the biomedical domain.
IIT-UHH at SemEval-2017 Task 3: Exploring Multiple Features for Community Question Answering and Implicit Dialogue Identification
In this paper we present the system for Answer Selection and Ranking in Community Question Answering, which we build as part of our participation in SemEval-2017 Task 3.
A Web-based Tool for the Integrated Annotation of Semantic and Syntactic Structures
We introduce the third major release of WebAnno, a generic web-based annotation tool for distributed teams.
