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Related Questions
- What are the common risks of relying on domain-specific ontologies and taxonomies in fine-tuning pipelines, and how can they be addressed?
- How do domain-specific ontologies and taxonomies impact the generalizability of fine-tuned models, and what strategies can be used to mitigate this limitation?
- What are the potential biases introduced by domain-specific ontologies and taxonomies, and how can they be corrected or avoided?
- Can you explain how the quality of domain-specific ontologies and taxonomies affects the performance of fine-tuned models, and what are the implications for model deployment?
- How do domain-specific ontologies and taxonomies interact with other factors that influence model performance, such as data quality and quantity?
- What are the trade-offs between using domain-specific ontologies and taxonomies versus more general-purpose knowledge representations in fine-tuning pipelines?
- Can you discuss the role of human judgment and expertise in selecting and refining domain-specific ontologies and taxonomies, and how this can impact model performance?
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