activity
20192026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 720 across the 43 of their papers we have counts for

collaborators
Showing 2026 · cs.CLShow all

12 papers · 2 filters

cs.CL2026

Measuring Research Progress and Linguistic Inclusion in Low-Resource Languages

Atnafu Lambebo Tonja, Tadesse Destaw Belay, Jesujoba Oluwadara Alabi +6

Large Language Models (LLMs) have accelerated research on low-resource and multilingual NLP, but their effectiveness in creating an equitable landscape remains unmapped. We analyze…

cs.CL2026

AfriGuard: Safety and Robust Refusal For African Languages

Israel Abebe Azime, Jesujoba O. Alabi, Iffat Maab +20

Large language models (LLMs) designed to interact with users are typically trained to respond appropriately to harmful or toxic content. However, ensuring appropriate responses bec…

cs.CL2026

Cultivar: A Contrastive and Locale-Oriented Translation Benchmark for Investigating Contamination and Localisation Robustness

Pinzhen Chen, Koel Dutta Chowdhury, Xiaoya Xu +20

Multilingual translation benchmarks are typically sourced in English and translated into other languages, treating language pairs as the unit of evaluation---a design that is prone…

cs.CL2026

From Monolingual to Multilingual: Evaluating Mamba for ASR in South African Languages

Jesujoba O. Alabi, Julian Herreilers, Badr M. Abdullah +1

Recent advances in automatic speech recognition (ASR) have explored different sequence models, including Conformer-based models and newer state space models such as Mamba. Although…

cs.CL2026

A Mechanistic Understanding of Pronoun Fidelity in LLMs

Katharina Trinley, Jesujoba O. Alabi, Dietrich Klakow +1

Faithful and robust pronoun use is important for fair and coherent generations, yet large language models largely fail when multiple referents use different pronouns. To study the…

cs.CL2026

OpenBibleTTS: Large-Scale Speech Resources and TTS Models for Low-Resource Languages

David Guzmán, Luel Hagos Beyene, Jesujoba Oluwadara Alabi +3

Recent advances in neural text-to-speech (TTS) and multilingual speech generation have substantially improved synthetic speech quality, yet these gains remain unevenly distributed…

cs.CL2026

AfrIFact: Cultural Information Retrieval, Evidence Extraction and Fact Checking for African Languages

Israel Abebe Azime, Jesujoba Oluwadara Alabi, Crystina Zhang +16

Assessing the veracity of a claim made online is a complex and important task with real-world implications. When these claims are directed at communities with limited access to inf…

cs.CL2026

Saar-Voice: A Multi-Speaker Saarbrücken Dialect Speech Corpus

Lena S. Oberkircher, Jesujoba O. Alabi, Dietrich Klakow +1

Natural language processing (NLP) and speech technologies have made significant progress in recent years; however, they remain largely focused on standardized language varieties. D…

cs.CL2026

YoNER: A New Yorùbá Multi-domain Named Entity Recognition Dataset

Peace Busola Falola, Jesujoba O. Alabi, Solomon O. Akinola +3

Named Entity Recognition (NER) is a foundational NLP task, yet research in Yorùbá has been constrained by limited and domain-specific resources. Existing resources, such as Masakha…

cs.CL2026

Ethio-ASR: Joint Multilingual Speech Recognition and Language Identification for Ethiopian Languages

Badr M. Abdullah, Israel Abebe Azime, Atnafu Lambebo Tonja +14

We present Ethio-ASR, a suite of multilingual CTC-based automatic speech recognition (ASR) models jointly trained on five Ethiopian languages: Amharic, Tigrinya, Oromo, Sidaama, an…

cs.CL2026

Afri-MCQA: Multimodal Cultural Question Answering for African Languages

Atnafu Lambebo Tonja, Srija Anand, Emilio Villa-Cueva +16

Africa is home to over one-third of the world's languages, yet remains underrepresented in AI research. We introduce Afri-MCQA, the first Multilingual Cultural Question-Answering b…

cs.CL2026

CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data

Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett +94

Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heter…