Mitigating Bias Through Data Diversity
Data bias and data diversity are interconnected issues in LLM training. A lack of diversity can foster bias; for example, an overreliance on English-centric data leads to cultural bias. Consequently, increasing the diversity of the training data, especially in terms of language, can be an effective strategy for mitigating such biases.
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Mitigating Bias Through Data Diversity
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