Papers by Meriem Beloucif
BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages (2025.acl-long)
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Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin, Jan Philip Wahle, Terry Ruas, Meriem Beloucif, Christine de Kock, Nirmal Surange, Daniela Teodorescu, Ibrahim Said Ahmad, David Ifeoluwa Adelani, Alham Fikri Aji, Felermino D. M. A. Ali, Ilseyar Alimova, Vladimir Araujo, Nikolay Babakov, Naomi Baes, Ana-Maria Bucur, Andiswa Bukula, Guanqun Cao, Rodrigo Tufiño, Rendi Chevi, Chiamaka Ijeoma Chukwuneke, Alexandra Ciobotaru, Daryna Dementieva, Murja Sani Gadanya, Robert Geislinger, Bela Gipp, Oumaima Hourrane, Oana Ignat, Falalu Ibrahim Lawan, Rooweither Mabuya, Rahmad Mahendra, Vukosi Marivate, Alexander Panchenko, Andrew Piper, Charles Henrique Porto Ferreira, Vitaly Protasov, Samuel Rutunda, Manish Shrivastava, Aura Cristina Udrea, Lilian Diana Awuor Wanzare, Sophie Wu, Florian Valentin Wunderlich, Hanif Muhammad Zhafran, Tianhui Zhang, Yi Zhou, Saif M. Mohammad
| Challenge: | Emotion recognition is an umbrella term for several NLP tasks, but most work on high-resource languages has focused on low-resourced languages. |
| Approach: | They propose to use emotion recognition to describe perceived emotions in 28 different languages and across several domains to identify and annotate the datasets. |
| Outcome: | The proposed datasets cover low-resource languages from Africa, Asia, Eastern Europe, and Latin America, with instances labeled by fluent speakers. |
AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages (2025.naacl-long)
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Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele, David Ifeoluwa Adelani, Ibrahim Said Ahmad, Saminu Mohammad Aliyu, Paul Röttger, Abigail Oppong, Andiswa Bukula, Chiamaka Ijeoma Chukwuneke, Ebrahim Chekol Jibril, Elyas Abdi Ismail, Esubalew Alemneh, Hagos Tesfahun Gebremichael, Lukman Jibril Aliyu, Meriem Beloucif, Oumaima Hourrane, Rooweither Mabuya, Salomey Osei, Samuel Rutunda, Tadesse Destaw Belay, Tadesse Kebede Guge, Tesfa Tegegne Asfaw, Lilian Diana Awuor Wanzare, Nelson Odhiambo Onyango, Seid Muhie Yimam, Nedjma Ousidhoum
| Challenge: | Hate speech and abusive language are global phenomena that need sociocultural background knowledge to be understood, identified, and moderated. |
| Approach: | They propose to use a multilingual dataset to collect hate speech and abusive language in 15 African languages to help improve model performance. |
| Outcome: | The proposed datasets are based on tweets annotated by native speakers familiar with the regional culture and show that they perform well in low-resource settings. |
Building Better: Avoiding Pitfalls in Developing Language Resources when Data is Scarce (2025.acl-long)
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| Challenge: | Language is a powerful means of communication and should be regarded as more than just a collection of tokens. |
| Approach: | They collect feedback from individuals directly involved in and impacted by NLP artefacts for medium- and low-resource languages and highlight key issues related to data quality, cultural appropriateness and ethics of common annotation practices. |
| Outcome: | The findings highlight key issues related to data quality, cultural appropriateness, and ethics of common annotation practices. |
Which is Better for Deep Learning: Python or MATLAB? Answering Comparative Questions in Natural Language (2021.eacl-demos)
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Viktoriia Chekalina, Alexander Bondarenko, Chris Biemann, Meriem Beloucif, Varvara Logacheva, Alexander Panchenko
| Challenge: | Comparative QA is a challenging task since it requires collecting evidence from many different sources. |
| Approach: | They propose a natural language interface for comparative QA that can be used in personal assistants, chatbots, and similar NLP devices. |
| Outcome: | The proposed system can be used in personal assistants, chatbots, and similar NLP devices. |
Elvis vs. M. Jackson: Who has More Albums? Classification and Identification of Elements in Comparative Questions (2022.lrec-1)
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| Challenge: | Comparative Question Answering (cQA) is the task of providing accurate answers to questions . most question answering systems focus on answering factoid questions, but they fail at answering comparative questions in an efficient argumentative manner. |
| Approach: | They propose two new open-domain datasets for identifying and labeling comparative questions . they use a binary classification task and an unsupervised sequence labeling task . |
| Outcome: | The proposed datasets reach close-to-human results on a binary classification task with a neural model using ALBERT embeddings. |
SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 13 Languages (2024.findings-acl)
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Nedjma Ousidhoum, Shamsuddeen Muhammad, Mohamed Abdalla, Idris Abdulmumin, Ibrahim Ahmad, Sanchit Ahuja, Alham Aji, Vladimir Araujo, Abinew Ayele, Pavan Baswani, Meriem Beloucif, Chris Biemann, Sofia Bourhim, Christine Kock, Genet Dekebo, Oumaima Hourrane, Gopichand Kanumolu, Lokesh Madasu, Samuel Rutunda, Manish Shrivastava, Thamar Solorio, Nirmal Surange, Hailegnaw Tilaye, Krishnapriya Vishnubhotla, Genta Winata, Seid Yimam, Saif Mohammad
| Challenge: | SemRel datasets are annotated by native speakers across 13 languages . they are used to characterise the relationship between two units of text . |
| Approach: | They propose to use a semantic relatedness dataset to measure the degree of semantic textual relatedness between sentences in Afrikaans, Algerian Arabic, Amharic, English, Hausa, Hindi, Indonesian, Kinyarwanda, Marathi, Moroccan Arabic, Modern Standard Arabic, Spanish, and Telugu. |
| Outcome: | The proposed datasets are annotated by native speakers across 13 languages and represent the semantic relatedness of 13 languages. |
Probing Pre-trained Language Models for Semantic Attributes and their Values (2021.findings-emnlp)
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| Challenge: | Pretrained language models (PTLMs) are used for many tasks including syntax, semantics and commonsense. |
| Approach: | They propose to integrate semantic attributes and their values into pretrained language models to improve their performance on many natural language processing tasks. |
| Outcome: | The proposed model performs better on masked tokens than humans on this task. |
AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages (2023.emnlp-main)
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Shamsuddeen Muhammad, Idris Abdulmumin, Abinew Ayele, Nedjma Ousidhoum, David Adelani, Seid Yimam, Ibrahim Ahmad, Meriem Beloucif, Saif Mohammad, Sebastian Ruder, Oumaima Hourrane, Alipio Jorge, Pavel Brazdil, Felermino Ali, Davis David, Salomey Osei, Bello Shehu-Bello, Falalu Lawan, Tajuddeen Gwadabe, Samuel Rutunda, Tadesse Belay, Wendimu Messelle, Hailu Balcha, Sisay Chala, Hagos Gebremichael, Bernard Opoku, Stephen Arthur
| Challenge: | Africa has the highest linguistic diversity among all continents. |
| Approach: | They introduce a sentiment analysis benchmark that contains >110,000 tweets in 14 African languages . they describe the data collection methodology, annotation process, and challenges . |
| Outcome: | The proposed dataset contains >110,000 tweets in 14 African languages . the tweets were annotated by native speakers and used in the shared task . |
Visualising Policy-Reward Interplay to Inform Zeroth-Order Preference Optimisation of Large Language Models (2025.findings-acl)
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| Challenge: | ZOPrO is a novel algorithm designed for *Preference Optimisation* in large language models. |
| Approach: | They propose a ZO algorithm designed for *Preference Optimisation* in LLMs that uses function evaluations instead of gradients to reduce memory usage. |
| Outcome: | The proposed method improves reward signals while achieving convergence times comparable to first-order methods. |
WikiBank: Using Wikidata to Improve Multilingual Frame-Semantic Parsing (2020.lrec-1)
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| Challenge: | Frame-semantic annotations exist for a tiny fraction of the world’s languages, however, Wikidata provides a common, distant supervision signal for semantic parsers. |
| Approach: | They propose a multilingual resource with partial semantic dependency structures that can be used to extend pre-existing resources rather than creating new man-made resources from scratch. |
| Outcome: | The proposed resource can be used to augment pre-existing resources or reduce the annotation effort for low-resource languages. |
BERTie Bott’s Every Flavor Labels: A Tasty Introduction to Semantic Role Labeling for Galician (2023.emnlp-main)
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| Challenge: | Existing corpora, WordNet, and dependency parsing are used to build a semantic role labeling system. |
| Approach: | They use existing corpora, WordNet, and dependency parsing to build a Galician dataset for training semantic role labeling systems. |
| Outcome: | The proposed model outperforms the 2009 CoNLL Shared Task by 0.83 on Spanish datasets. |