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Wazobia Eval is a benchmark designed to evaluate AI models on emotion understanding, sarcasm detection, and cultural reasoning in Nigerian Pidgin, aiming to advance NLP capabilities for this language.
This paper presents an empirical study on sentiment classifier behavior with sarcastic and AI-paraphrased social text, revealing lower confidence on sarcasm, higher accuracy on AI paraphrases, and an abstention method that improves performance by handling low-confidence inputs.