Papers by Jamell Dacon
Does Gender Matter? Towards Fairness in Dialogue Systems (2020.coling-main)
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| Challenge: | Recent studies have shown that AI is unfair in many real-world applications such as computer vision and recommendations. |
| Approach: | They propose to use a benchmark dataset to study the fairness of dialogue systems to understand their bias. |
| Outcome: | The proposed methods reduce the bias in dialogue systems significantly. |
Evaluating and Mitigating Inherent Linguistic Bias of African American English through Inference (2022.coling-1)
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| Challenge: | Recent studies show that NLP models trained on standard English produce biased outcomes against underrepresented English varieties. |
| Approach: | They propose a morphosyntactically-informed rule-based translation method that uses a greedy algorithm to debiase NLP models. |
| Outcome: | The proposed framework outperforms large language models while maintaining or improving the prediction performance. |