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Open-ended text generation in isiZulu: decoding strategies for a morphologically rich low-resource language
Generating high-quality text in under-resourced and morphologically complex languages like isiZulu is vital for natural language processing advancements, yet such languages remain underexplored. Addressing this challenge could improve text generation performance and enable broader applications. This...
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Department of Statistical Sciences
2026
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