activity
20182025
most citedSCoT: Sense Clustering over Time: a tool for the analysis of lexical change

6 citations · 8 across the 4 of their papers we have counts for

collaborators

13 papers

cs.CL2025

The Rise of AfricaNLP: A Survey of Contributions, Contributors, Community Impact, and Bibliometric Analysis

Tadesse Destaw Belay, Kedir Yassin Hussen, Sukairaj Hafiz Imam +11

Natural Language Processing (NLP) is undergoing constant transformation, as Large Language Models (LLMs) are driving daily breakthroughs in research and practice. In this regard, t…

cs.CY2025

FASCIST-O-METER: Classifier for Neo-fascist Discourse Online

Rudy Alexandro Garrido Veliz, Martin Semmann, Chris Biemann +1

Neo-fascism is a political and societal ideology that has been having remarkable growth in the last decade in the United States of America (USA), as well as in other Western societ…

cs.CL2022

The Effect of Normalization for Bi-directional Amharic-English Neural Machine Translation

Tadesse Destaw Belay, Atnafu Lambebo Tonja, Olga Kolesnikova +5

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. Nowadays,…

cs.CL20226 cited

SCoT: Sense Clustering over Time: a tool for the analysis of lexical change

Christian Haase, Saba Anwar, Seid Muhie Yimam +2

We present Sense Clustering over Time (SCoT), a novel network-based tool for analysing lexical change. SCoT represents the meanings of a word as clusters of similar words. It visua…

cs.CL2021

MasakhaNER: Named Entity Recognition for African Languages

David Ifeoluwa Adelani, Jade Abbott, Graham Neubig +58

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 en…

cs.CL2020

UHH-LT at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language Detection

Gregor Wiedemann, Seid Muhie Yimam, Chris Biemann

Fine-tuning of pre-trained transformer networks such as BERT yield state-of-the-art results for text classification tasks. Typically, fine-tuning is performed on task-specific trai…