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Natural Language Processing
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In CRF training, loss = logZ − gold_score. When the model is trained well and these two values become equal, what does it mean?
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BERT masks 15% of tokens during pre-training, but only uses [MASK] for 80% of them. What happens to the other 20%?
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In TF-IDF, what does a high IDF score for a word mean?
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To answer "man is to woman as king is to ?", word embeddings use vector arithmetic. Which are correct?
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What does BPE (Byte-Pair Encoding) do at each training step?
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In BERT's tokenizer, what does the
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What is the purpose of gradient clipping during BiLSTM training?
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How is GloVe different from Word2Vec in terms of training?
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"Fertility" measures how many tokens a tokenizer produces per word on average. Which statements are true?
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How does subword tokenization handle words that were never seen during training?
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