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Related Questions
- Can large language models (LLMs) learn to recognize and understand new homographs that are not present in their training data?
- Do LLMs have the ability to generalize and adapt to novel homographs that are outside of their training scope?
- How do LLMs handle out-of-vocabulary (OOV) words, including homographs, that are not seen during training?
- Can LLMs learn to disambiguate homographs with multiple meanings and adapt to new contexts?
- What are the limitations of LLMs in learning to generalize and adapt to new homographs?
- Can LLMs be fine-tuned to learn new homographs and adapt to changing language patterns?
- How do LLMs' ability to generalize and adapt to new homographs impact their performance in real-world applications?
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