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Related Questions
- How can LLMs handle and adapt to new, uncommon words within a domain?
- Can context-dependent prediction methods help resolve out-of-vocabulary challenges in language models?
- What role can pre-trained language models, such as masked language models, play in reducing unknown word tokens?
- Would incorporating large parallel corpora improve an LLM's ability to map out of vocabulary words and their subwords?
- How might unsupervised learning or open-vocab learning mitigate some of these out-of- vocabulary weaknesses?
- Why do OOV words consistently affect test datasets, thereby impacting an evaluation metric during model optimization time?
- Can one use auxiliary methods, combined with some adaptation of this auxiliary strategy?
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