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Meriem Beloucif

8 accepted papers

2025

AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages

Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele, David Ifeoluwa Adelani, Ibrahim Said Ahmad, Saminu Mohammad Aliyu +21
NAACL 2025long

Hate speech and abusive language are global phenomena that need socio-cultural background knowledge to be understood, identified, and moderated. However, in many regions of the Global South, there have been several documented occurrences of (1) absence of moderation and (2) censorship due to the rel…

Cited by 2Source ↗PDF ↗code ↗Scholar ↗
2025

BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages

Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin, Jan Philip Wahle, Terry Ruas, Meriem Beloucif +42
ACL 2025long

People worldwide use language in subtle and complex ways to express emotions. Although emotion recognition–an umbrella term for several NLP tasks–impacts various applications within NLP and beyond, most work in this area has focused on high-resource languages. This has led to significant disparities…

Cited by 0Source ↗PDF ↗code ↗Scholar ↗
2025

Building Better: Avoiding Pitfalls in Developing Language Resources when Data is Scarce

Nedjma Ousidhoum, Meriem Beloucif, Saif M. Mohammad
ACL 2025long

Language is a form of symbolic capital that affects people’s lives in many ways (Bourdieu1977,1991). As a powerful means of communication, it reflects identities, cultures, traditions, and societies more broadly. Therefore, data in a given language should be regarded as more than just a collection o…

Cited by 0Source ↗PDF ↗Scholar ↗
2025

Visualising Policy-Reward Interplay to Inform Zeroth-Order Preference Optimisation of Large Language Models

Alessio Galatolo, Zhenbang Dai, Katie Winkle, Meriem Beloucif
ACL 2025finding

Fine-tuning Large Language Models (LLMs) with first-order methods like back-propagation is computationally intensive. Zeroth-Order (ZO) optimisation uses function evaluations instead of gradients, reducing memory usage, but suffers from slow convergence in high-dimensional models. As a result, ZO re…

Cited by 0Source ↗PDF ↗code ↗Scholar ↗
2024

SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 13 Languages

Nedjma Ousidhoum, Shamsuddeen Muhammad, Mohamed Abdalla, Idris Abdulmumin, Ibrahim Ahmad, Sanchit Ahuja +21
ACL 2024findings

Exploring and quantifying semantic relatedness is central to representing language and holds significant implications across various NLP tasks. While earlier NLP research primarily focused on semantic similarity, often within the English language context, we instead investigate the broader phenomeno…

Cited by 10Source ↗PDF ↗code ↗Scholar ↗
2023

AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages

Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele, Nedjma OUSIDHOUM, David Ifeoluwa Adelani, Seid Muhie Yimam +21
EMNLP 2023long main

Africa is home to over 2,000 languages from over six language families and has the highest linguistic diversity among all continents. This includes 75 languages with at least one million speakers each. Yet, there is little NLP research conducted on African languages. Crucial in enabling such researc…

Cited by 0Source ↗code ↗Scholar ↗
2023

BERTie Bott's Every Flavor Labels: A Tasty Introduction to Semantic Role Labeling for Galician

Micaella Bruton, Meriem Beloucif
EMNLP 2023long main

In this paper, we leverage existing corpora, WordNet, and dependency parsing to build the first Galician dataset for training semantic role labeling systems in an effort to expand available NLP resources. Additionally, we introduce verb indexing, a new pre-processing method, which helps increase the…

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2021

Probing Pre-trained Language Models for Semantic Attributes and their Values

Meriem Beloucif, Chris Biemann
EMNLP 2021finding

Pretrained language models (PTLMs) yield state-of-the-art performance on many natural language processing tasks, including syntax, semantics and commonsense. In this paper, we focus on identifying to what extent do PTLMs capture semantic attributes and their values, e.g., the correlation between ric…

Cited by 12Source ↗PDF ↗code ↗Scholar ↗