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Advantages vs. Disadvantages
Neural language models have many advantages over the n-gram language models. Compared to n-gram models, neural language models can handle much longer histories, can generalize better over contexts of similar words, and are more accurate at word-prediction.
On the other hand, neural net language models are much more complex, slower to train, and less interpretable than n-gram models, so for many (especially smaller) tasks an n-gram language model is still the right tool.
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Advantages vs. Disadvantages
Mini example
Bengio et al. (2003) Feed-Forward Neural Language Model
A language model is designed using a feedforward network architecture. It is trained to predict the next word by looking at a fixed-size window of the N preceding words (e.g., N=4). What is the most significant architectural limitation of this approach for modeling language?
Consider a feedforward neural network designed to predict the next word based on a fixed window of the three preceding words. Arrange the following computational steps in the correct order, from initial input to final output.
Function of Word Vector Representations