activity
20202026
most citedParticipatory Research for Low-resourced Machine Translation: A Case Study in African Languages

7 citations · 22 across the 40 of their papers we have counts for

collaborators

38 papers

cs.CL2026

The Illusion of Cross-Lingual Safety in Low-Resource Languages

Abigail Oppong, P Sam Sahil, Tadesse Destaw Belay +12

Safety alignment in large language models (LLMs) is largely developed in English, assuming these safeguards generalize across multilingual settings. However, this assumption remain…

cs.CL2026

LLM Safety Alignment in Low-Resource Languages: A Systematic Literature Review

Valdini Douglace Lemofouet, Blessing Ngozi Uzor, Paula Chikaodinaka Anyanwu +9

Large Language Models (LLMs) have achieved substantial progress in safety alignment, yet their safety guarantees remain significantly weaker in low-resource and multilingual settin…

cs.LG2026

Bias Redistribution in Visual Machine Unlearning: Does Forgetting One Group Harm Another?

Yunusa Haruna, Adamu Lawan, Ibrahim Haruna Abdulhamid +4

Machine unlearning enables models to selectively forget training data, driven by privacy regulations such as GDPR and CCPA. However, its fairness implications remain underexplored:…

cs.CL2026

SemEval-2026 Task 3: Dimensional Aspect-Based Sentiment Analysis (DimABSA)

Liang-Chih Yu, Jonas Becker, Shamsuddeen Hassan Muhammad +14

We present the SemEval-2026 shared task on Dimensional Aspect-Based Sentiment Analysis (DimABSA), which improves traditional ABSA by modeling sentiment along valence-arousal (VA) d…

cs.CL2026

DimStance: Multilingual Datasets for Dimensional Stance Analysis

Jonas Becker, Liang-Chih Yu, Shamsuddeen Hassan Muhammad +14

Stance detection is an established task that classifies an author's attitude toward a specific target into categories such as Favor, Neutral, and Against. Beyond categorical stance…

cs.CL2026

PingPong: A Natural Benchmark for Multi-Turn Code-Switching Dialogues

Mohammad Rifqi Farhansyah, Hanif Muhammad Zhafran, Farid Adilazuarda +6

Code-switching is a widespread practice among the world's multilingual majority, yet few benchmarks accurately reflect its complexity in everyday communication. We present PingPong…