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Related Questions
- What are the primary challenges in integrating entity recognition and relation extraction in LLMs, and how do they impact computational efficiency?
- How do LLMs handle the increased computational complexity of entity recognition and relation extraction, and what strategies are used to mitigate this?
- What are the trade-offs between the accuracy of entity recognition and relation extraction versus the computational efficiency of LLMs when handling large-scale datasets?
- Can you explain the impact of entity recognition and relation extraction on the training time and memory requirements of LLMs?
- How do LLMs handle the curse of dimensionality when dealing with large-scale datasets and complex entity recognition and relation extraction tasks?
- What are some techniques used to parallelize entity recognition and relation extraction in LLMs, and how do they improve computational efficiency?
- How do LLMs balance the need for accurate entity recognition and relation extraction with the need for efficient processing of large-scale datasets?
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