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Related Questions
- What are the potential biases that can be introduced into a language model through inadequate training data?
- How does the quality of human annotation impact the accuracy of a language model's understanding of nuances in language?
- What are some strategies for mitigating the impact of noisy or biased training data on a language model's performance?
- Can you explain the concept of 'annotation quality' in the context of language model training, and how it affects the model's ability to capture subtle differences in language?
- How does the annotation process for a language model affect its ability to understand context-dependent language?
- What are the consequences of using low-quality training data on a language model's performance in capturing subtle differences in language?
- Can you discuss the trade-offs between data quantity, data quality, and annotation quality in language model training, and how they impact the model's performance in capturing subtle differences in language?
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