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Related Questions
- What is the average attention span of LLMs when encountering unknown words and entities?
- Do attention-based LLMs employ subword or byte-pair encoding to represent out-of-vocabulary words?
- Can LLMs handle mentions of specific individuals, companies, or events not covered by their training data?
- How do attention-based LLMs infer meaning for entities not explicitly present in their training data?
- Are there any differences in how attention-based LLMs handle named entities versus pronouns in unknown entities?
- What is the impact of word embeddings on the performance of LLMs in handling out-of-vocabulary words and entities?
- Can LLMs leverage external knowledge sources to supplement their understanding of unknown entities and words?
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