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Karim Lasri

6 accepted papers

2024

NaijaHate: Evaluating Hate Speech Detection on Nigerian Twitter Using Representative Data

Manuel Tonneau, Pedro Quinta De Castro, Karim Lasri, Ibrahim Farouq, Lakshmi Subramanian, Victor Orozco-Olvera +1
ACL 2024long

To address the global issue of online hate, hate speech detection (HSD) systems are typically developed on datasets from the United States, thereby failing to generalize to English dialects from the Majority World. Furthermore, HSD models are often evaluated on non-representative samples, raising co…

Cited by 5Source ↗PDF ↗code ↗Scholar ↗
2023

EconBERTa: Towards Robust Extraction of Named Entities in Economics

Karim Lasri, Pedro Vitor Quinta de Castro, Mona Schirmer, Luis Eduardo San Martin, Linxi Wang, Tomáš Dulka +4
EMNLP 2023long findings

Adapting general-purpose language models has proven to be effective in tackling downstream tasks within specific domains. In this paper, we address the task of extracting entities from the economics literature on impact evaluation. To this end, we release EconBERTa, a large language model pretrained…

Cited by 0Source ↗Scholar ↗
2022

Does BERT really agree ? Fine-grained Analysis of Lexical Dependence on a Syntactic Task

Karim Lasri, Alessandro Lenci, Thierry Poibeau
ACL 2022findings

Although transformer-based Neural Language Models demonstrate impressive performance on a variety of tasks, their generalization abilities are not well understood. They have been shown to perform strongly on subject-verb number agreement in a wide array of settings, suggesting that they learned to t…

Cited by 21Source ↗PDF ↗code ↗Scholar ↗
2022

Probing for the Usage of Grammatical Number

Karim Lasri, Tiago Pimentel, Alessandro Lenci, Thierry Poibeau, Ryan Cotterell
ACL 2022long

A central quest of probing is to uncover how pre-trained models encode a linguistic property within their representations. An encoding, however, might be spurious—i.e., the model might not rely on it when making predictions. In this paper, we try to find an encoding that the model actually uses, int…

Cited by 59Source ↗PDF ↗Scholar ↗
2022

Subject Verb Agreement Error Patterns in Meaningless Sentences: Humans vs. BERT

Karim Lasri, Olga Seminck, Alessandro Lenci, Thierry Poibeau
COLING 2022main

Both humans and neural language models are able to perform subject verb number agreement (SVA). In principle, semantics shouldn’t interfere with this task, which only requires syntactic knowledge. In this work we test whether meaning interferes with this type of agreement in English in syntactic str…

Cited by 4Source ↗PDF ↗Scholar ↗