Papers by Macton Mgonzo
UbuntuGuard: A Culturally-Grounded Policy Benchmark for Equitable AI Safety in African Languages. (2026.findings-acl)
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Tassallah Abdullahi, Macton Mgonzo, Mardiyyah Oduwole, Paul Okewunmi, Abraham Toluwase Owodunni, Ritambhara Singh, Carsten Eickhoff
| Challenge: | Current guardian models are predominantly Western-centric and optimized for high-resource languages . low-resourced African languages are vulnerable to evolving harms, cross-lingual failures, cultural misalignment . |
| Approach: | They propose a policy-based safety benchmark for African languages built from adversarial queries authored by 155 domain experts across sensitive fields. |
| Outcome: | The proposed model overestimates multilingual safety, cross-lingual transfer provides partial but insufficient coverage, and dynamic models struggle to localize African-language contexts. |
Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance (2025.findings-emnlp)
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| Challenge: | a new approach to training with binary relevance labels uses synthetic data . contrastive learning with binary correlations leaves out subtle nuances useful for ranking . |
| Approach: | They propose to use waterstein distance as a loss function for training transformer-based retrievers with graduated relevance labels instead of real documents. |
| Outcome: | The proposed method outperforms conventional training with InfoNCE by a large margin on MARCO and BEIR benchmarks without using real documents. |